Abstract:

Method and apparatus for generating and selecting low-frequency
time-domain signals capable of transducing a mammalian system, to produce
an agent-specific effect on the system, are disclosed. Low-frequency
time-domain signals are generated in the presence of an injected magnetic
stimulus, and the resulting signals are selected by a scoring algorithm,
and optionally, by testing each signal identified by the scoring
algorithm for its ability to produce an agent-specific response in a in
vitro system containing components that are responsive to the agent. The
selected signals are used to transduce the mammalian system by applying
the signals to an electromagnetic transduction coil that holds the
sample.

Claims:

1. A method for generating a signal capable of producing an agent-specific
effect on a mammalian system, when the system is transduced by the signal
within the environment of an electromagnetic tranducer, comprising:(a)
placing a sample containing the agent in a sample container having both
magnetic and electromagnetic shielding, wherein the sample acts as a
signal source for low-frequency molecular signals, and wherein the
magnetic shielding is external to a cryogenic container;(b) injecting a
stimulus magnetic field into the sample, under a selected stimulus
magnetic field condition,(c) recording a low-frequency, time-domain
signal composed of sample source radiation superimposed on the injected
stimulus magnetic field in the cryogenic container,(d) repeating steps
(b) and (c) at each of a plurality of different stimulus magnetic field
conditions,(e) identifying from among the signals recorded in step (c),
one or more signals having the highest signal scores when analyzed by a
scoring algorithm that measures the number of low-frequency components
above a given threshold in a recorded signal,(f) testing each signal
identified in step (e) for its ability to produce an agent-specific
response in a in vitro system containing components that are responsive
to the agent, when the in vitro system is transduced with the signal
within the environment of an electromagnetic tranducer, and(g) selecting
one or more signals that produce the greatest agent-specific transduction
effect in the in vitro system.

2. The method of claim 1, wherein the different conditions of stimulus
magnetic field include conditions selected from the group consisting
of:(i) white noise, injected at voltage level calculated to produce a
selected magnetic field at the sample of between 0 and 1 G (Gauss), (ii)
a DC offset, injected at voltage level calculated to produce a selected
magnetic field at the sample of between 0 and 1 G, and (iii) sweeps over
a low-frequency range, injected successively over a sweep range between
at least about 0-1 kHz, and at an injected voltage calculated to produce
a selected magnetic field at the sample of between 0 and 1 G.

3. The method of claim 2, wherein the different conditions of stimulus
magnetic field include a DC offset, injected at voltage level calculated
to produce a selected magnetic field at the sample of between 0 and 1 G.

4. The method of claim 2, wherein the different conditions of stimulus
magnetic field include successive sweeps over a low-frequency range
between at least about 0-1 kHz, and at an injected voltage calculated to
produce a selected magnetic field at the sample of between 0 and 1 G.

5. The method of claim 1, wherein step (f) further includes, after testing
a time-domain signal for its ability to produce an agent-specific
response in a in vitro system containing components that are responsive
to the agent, testing the ability of signal to produce an agent-specific
response under varying transduction conditions, including variations in
transduction voltage applied within the environment of an electromagnetic
tranducer, thus to optimize transduction conditions for transduction in
the mammalian system.

6. The method of claim 1, wherein step (e) is carried out by a method
selected from the group consisting of:(i) autocorrelating the time domain
signal, generating an FFT (Fast Fourier Transform) of the autocorrelated
signal over a selected frequency range within the range DC to 8 kHz,
assigning to the FFT signal a score related to a number of peaks above a
mean average noise value, and selecting a time-domain signal based on the
score;(ii) calculating a pair of phase spaces for two time domain
signals, and performing a mathematical comparison to provide a measure of
difference between the two;(iii) generating a histogram that shows, for
each event bin f over a selected frequency range within a range DC to 8
kHz, a number of event counts in each bin, where f is a sampling rate for
sampling the time domain signal, assigning to the histogram, a score
related to number of bins that are above a given threshold; and selecting
a time-domain signal based on the score;(iv) cross-correlating a small
block of data near the beginning of the time domain signal with the
remainder of the time series, and counting the occurrences that the
resulting cross-correlation surpasses a given threshold; and(v)
calculating a series of Fourier spectra of the time-domain signal over
each of multiple defined time periods, in a selected frequency range
between DC and 8 kHz, averaging the Fourier spectra; assigning to the
averaged FFT signal a score related to the number of peaks above a mean
average noise value, and selecting a time-domain signal based on the
score.

7. The method of claim 6, wherein step (e) is carried out by
autocorrelating the time domain signal, generating an FFT (Fast Fourier
Transform) of the autocorrelated signal over a selected frequency range
within the range DC to 8 kHz, assigning to the FFT signal a score related
to a number of peaks above a mean average noise value, and selecting a
time-domain signal based on the score;

8. The method of claim 1, wherein the electromagnetic transducer includes
a Helmholtz coil having a pair of aligned electromagnetic coils defining
an exposure station therebetween, constituting the environment of the
electromagnetic environment, and step (f) includes placing the in vitro
system within the aligned coils, and transducing the system with an
agent-specific time-domain signal identified in step (e).

9. The method of claim 1, wherein the agent is an anti-neoplastic drug
effective to promote tubulin aggregation in a cell-free in vitro system,
and step (f) includes placing a tubulin-containing composition within the
environment of the electromagnetic transducer, and transducing the
composition with an agent-specific time-domain signal identified in step
(e).

10. A method for generating signals capable of producing an agent-specific
effect on an in vitro or mammalian system when the system is transduced
by the signal within the environment of an electromagnetic transducer,
comprising:(a) placing a sample containing the agent in a container
having both magnetic and electromagnetic shielding, wherein the sample
acts as a signal source for molecular signals, and wherein the magnetic
shielding is external to a cryogenic container;(b) injecting a stimulus
magnetic field into the sample, a under selected stimulus magnetic field
condition selected from the group consisting of (i) white noise, injected
at voltage level calculated to produce a selected magnetic field at the
sample of between 0 and 1 G (Gauss), (ii) a DC offset, injected at
voltage level calculated to produce a selected magnetic field at the
sample of between 0 and 1 G, and (iii) sweeps over a low-frequency range,
injected successively over a sweep range between at least about 0-1 kHz,
and at an injected voltage calculated to produce a selected magnetic
field at the sample of between 0 and 1 G,(c) recording a low-frequency,
time-domain signal composed of sample source radiation superimposed on
the injected stimulus magnetic field in the cryogenic container,(d)
repeating steps (b) and (c) at each of a plurality of different stimulus
magnetic field conditions,(e) identifying from among the signals recorded
in step (c), one or more signals having the highest signal scores when
analyzed by a scoring algorithm that measures the number of low-frequency
components above a given threshold in a recorded signal, and(f)
transducing the in vitro or mammalian system by placing the system within
the environment of an electromagnetic transducer, and transducing the
sample with a signal identified in step (e).

11. The method of claim 10, wherein the different conditions of stimulus
magnetic field include a DC offset, injected at an offset voltage between
about +0.01 to +1 volt.

12. The method of claim 10, wherein the different conditions of stimulus
magnetic field include successive sweeps over a low-frequency range
between at least about 0-1 kHz, injected at a sweep voltage of between
+0.01 to +1 volt.

13. The method of claim 10, wherein step (e) is carried out by
autocorrelating the time domain signal, generating an FFT (Fast Fourier
Transform) of the autocorrelated signal over a selected frequency range
within the range DC to 8 kHz, assigning to the FFT signal a score related
to a number of peaks above a mean average noise value, and selecting a
time-domain signal based on the score;

14. The method of claim 10, wherein the electromagnetic transducer
includes a Helmholtz coil having a pair of aligned electromagnetic coils
defining an exposure station therebetween, constituting the environment
of the electromagnetic environment, and step (f) includes placing the
chemical, in vitro, or mammalian system within the aligned coils, and
transducing the system with an agent-specific time-domain signal
identified in step (e).

15. The method of claim 14, wherein the agent is an anti-neoplastic drug
effective to promote tubulin aggregation in an in vitro system, step (f)
includes placing a tubulin-containing composition within the environment
of the electromagnetic transducer, and transducing the composition with
an agent-specific time-domain signal identified in step (e) under
conditions effective to produce signal-dependent aggregation of the
tubulin in the composition.

16. Apparatus for producing low-frequency, time-domain signals that are
candidates for transducing an in vitro or mammalian system that is
responsive to the presence of a selected agent, comprising(a) a container
adapted for receiving a sample of an agent, the container having both
magnetic and electromagnetic shielding;(b) an adjustable-power source
operable to inject a stimulus magnetic field into the container, with a
sample in the container, at each of a plurality of selected stimulus
magnetic field conditions selected from the group consisting of (i) white
noise, injected at voltage level calculated to produce a selected
magnetic field at the sample of between 0 and 1 G (Gauss), (ii) a DC
offset, injected at voltage level calculated to produce a selected
magnetic field at the sample of between 0 and 1 G, and (iii) sweeps over
a low-frequency range, injected successively over a sweep range between
at least about 0-1 kHz, and at an injected voltage calculated to produce
a selected magnetic field at the sample of between 0 and 1 G,(c) a
detector for recording, at each of the different stimulus magnetic field
conditions injected by said power source, (b) the electromagnetic
time-domain signals composed of sample source radiation superimposed on
the injected stimulus magnetic fields,(d) a memory device for storing the
signals recorded by the detector, and(e) a computer operable to:(i)
retrieve time-domain signals stored in the memory device;(ii) analyzing
the retrieved time-domain signals by a scoring algorithm that measures
the number of low-frequency components above a given threshold in a
recorded signal, and(iii) identifying those time-domain signals having
the greatest number of low-frequency components above the threshold.

17. The apparatus of claim 16, wherein the container is an attenuation
tube having a sample-holding region, a magnetic shielding cage
surrounding the region, and a Faraday cage contained within the magnetic
shielding cage and also surrounding the region, the source of a Gaussian
noise includes a Gaussian noise generator and a Helmholtz coil which is
contained within the magnetic cage and the Faraday cage, and which
receives a noise output signal from the noise generator, and which
further includes, for use in removing stationary noise components in the
time-dependent signal, a signal inverter operatively connected to the
noise source and to the SQUID (Superconducting QUantum Interference
Device), for receiving Gaussian noise from the noise source and
outputting into the SQUID, Gaussian noise in inverted form with respect
to the Gaussian noise injected into the sample.

18. The apparatus of claim 16, wherein said power source if operable to
inject an offset voltage into the container, with a sample in the
container, at each of a plurality of selected offset voltages calculated
to produce a selected magnetic field at the sample of between 0 and 1 G.

19. The apparatus of claim 16, wherein said power source if operable to
inject generate successive sweeps over a sweep-frequency range between at
least about 0 and 1 kHz, at each of a plurality of different sweep
voltages calculated to produce a selected magnetic field at the sample of
between 0 and 1 G.

20. The apparatus of claim 16, wherein said computer, in analyzing the
retrieved time-domain signals is operable to apply an analysis algorithm
selected from the group consisting of:(i) autocorrelating the time domain
signal, generating an FFT (Fast Fourier Transform) of the autocorrelated
signal over a selected frequency range within the range DC to 8 kHz,
assigning to the FFT signal a store related to a number of peaks above a
mean average noise value, and selecting a time-domain signal based on the
score;(ii) calculating a pair of phase spaces for two time domain
signals, and performing a mathematical comparison to provide a measure of
difference between the two;(iii) generating a histogram that shows, for
each event bin f over a selected frequency range within a range DC to 8
kHz, a number of event counts in each bin, where f is a sampling rate for
sampling the time domain signal, assigning to the histogram, a score
related to number of bins that are above a given threshold; and selecting
a time-domain signal based on the score;(iv) cross-correlating a small
block of data near the beginning of the time domain signal with the
remainder of the time series, and counting the occurrences that the
resulting cross-correlation surpasses a given threshold; and(v)
calculating a series of Fourier spectra of the time-domain signal over
each of multiple defined time periods, in a selected frequency range
between DC and 8 kHz, averaging the Fourier spectra; assigning to the
averaged FFT signal a score related to the number of peaks above a mean
average noise value, and selecting a time-domain signal based on the
score.

21. The apparatus of claim 20, wherein said computer, in analyzing the
retrieved time-domain signals is operable to apply an analysis algorithm
that involves autocorrelating the time domain signal, generating an FFT
(Fast Fourier Transform) of the autocorrelated signal over a selected
frequency range within the range DC to 8 kHz, assigning to the FFT signal
a score related to a number of peaks above a mean average noise value,
and selecting a time-domain signal based on the score;

22. A system for producing an agent-specific effect on a mammalian system
comprising,(1) a storage medium having stored thereon, an agent-specific
low-frequency time-domain signal produced by the steps of:(a) placing a
sample to which the mammalian system is responsive in a sample container
having both magnetic and electromagnetic shielding, wherein the sample
acts as a signal source for low-frequency molecular signals, and wherein
the magnetic shielding is external to a cryogenic container;(b) injecting
a stimulus magnetic field into the sample, under a selected stimulus
magnetic field condition,(c) recording a low-frequency, time-domain
signal composed of sample source radiation superimposed on the injected
stimulus magnetic field in the cryogenic container,(d) repeating steps
(b) and (c) at each of a plurality of different stimulus magnetic field
conditions,(e) identifying from among the signals recorded in step (c),
one or more signals having the highest signal scores when analyzed by a
scoring algorithm that measures the number of low-frequency components
above a given threshold in a recorded signal,(f) testing each signal
identified in step (e) for its ability to produce an agent-specific
response in a in vitro system containing components that are responsive
to the agent, when the in vitro system is transduced by the signal within
the environment of an electromagnetic transducer,(2) an electromagnetic
transducer composed of one or more electromagnetic coils, said coils
having an interior region defining a transducer environment in which the
sample is received, and(3) an amplifier for amplifying the signal
received from the storage medium and supplying the amplified signal to
the transduction coil(s).

23. The apparatus of claim 22, wherein the different conditions of
stimulus magnetic field used in producing the agent-specific
low-frequency time-domain signal are selected from the group consisting
of:(i) white noise, injected at voltage level calculated to produce a
selected magnetic field at the sample of between 0 and 1 G (Gauss), (ii)
a DC offset, injected at voltage level calculated to produce a selected
magnetic field at the sample of between 0 and 1 G, and (iii) sweeps over
a low-frequency range, injected successively over a sweep range between
at least about 0-1 kHz, and at an injected voltage calculated to produce
a selected magnetic field at the sample of between 0 and 1 G.

24. The apparatus of claim 23, wherein the different conditions of
stimulus magnetic field used in producing the agent-specific
low-frequency time-domain signal include different conditions of stimulus
magnetic field include a DC offset, injected at a voltage calculated to
produce a selected magnetic field at the sample of between 0 and 1 G,

25. The apparatus of claim 23, wherein the different conditions of
stimulus magnetic field used in producing the agent-specific
low-frequency time-domain signal include successive sweeps over a
low-frequency range between at least about 0-1 kHz, injected at a sweep
voltage calculated to produce a selected magnetic field at the sample of
between 0 and 1 G.

26. The apparatus of claim 22, wherein the electromagnetic transducer
includes a Helmholtz coil having a pair of aligned electromagnetic coils
defining an interior region therebetween.

27. A storage medium having stored thereon, an agent-specific
low-frequency time-domain signal produced by the steps of:(a) placing a
sample to which the mammalian system is responsive in a sample container
having both magnetic and electromagnetic shielding, wherein the sample
acts as a signal source for low-frequency molecular signals, and wherein
the magnetic shielding is external to a cryogenic container;(b) injecting
a stimulus magnetic field into the sample, under a selected stimulus
magnetic field condition,(c) recording a low-frequency, time-domain
signal composed of sample source radiation superimposed on the injected
stimulus magnetic field in the cryogenic container,(d) repeating steps
(b) and (c) at each of a plurality of different stimulus magnetic field
conditions,(e) identifying from among the signals recorded in step (c),
one or more signals having the highest signal scores when analyzed by a
scoring algorithm that measures the number of low-frequency components
above a given threshold in a recorded signal,(f) testing each signal
identified in step (e) for its ability to produce an agent-specific
response in a in vitro system containing components that are responsive
to the agent, when the in vitro system is transduced by the signal within
the environment of an electromagnetic transducer.

28. The storage medium of claim 27, wherein the different conditions of
stimulus magnetic field used in producing the agent-specific
low-frequency time-domain signal are selected from the group consisting
of:

29. The storage medium of claim 28, wherein the different conditions of
stimulus magnetic field used in producing the agent-specific
low-frequency time-domain signal include different conditions of stimulus
magnetic field include a DC offset, injected at a voltage calculated to
produce a selected magnetic field at the sample of between 0 and 1 G.

30. The storage medium of claim 29, wherein the different conditions of
stimulus magnetic field used in producing the agent-specific
low-frequency time-domain signal include successive sweeps over a
low-frequency range between at least about 0-1 kHz, injected at a sweep
voltage calculated to produce a selected magnetic field at the sample of
between 0 and 1 G.

31. The storage medium of claim 28, wherein the agent-specific,
time-domain signal is generated from a sample of an anti-neoplastic agent
effective to promote tubulin aggregation in an in vitro system.

Description:

FIELD OF THE INVENTION

[0001]The present invention relate to signals readable by a system for
converting or transducing the signal into electromagnetic waves, and to
methods of producing and applying such signals.

BACKGROUND OF THE INVENTION

[0002]One of the accepted paradigms in the fields of chemistry and
biochemistry is that chemical or biochemical effector agents, e.g.,
molecules, interact with target systems through various physicochemical
forces, such as ionic, charge, or dispersion forces or through the
cleavage or formation of covalent or charge-induced bonds. These forces
may involve energy modes in either the effector agent or target system.

[0003]A corollary of this paradigm is the requirement, in effector-target
systems, of the effector agent in the target environment. However, what
is not known or understood is whether this requirement is related to the
actual presence of the effector, or whether it may be due, at least as to
certain effector functions, to the presence of energetic modes that are
characteristic of the effector. If effector function can be simulated, at
least in part, by certain characteristic energetic modes, it may be
possible to "simulate" the effect of the effector agent in a target
system by exposing the system to certain energetic modes that are
characteristic of the effector. If so, the questions that naturally arise
are: what effector-molecule energy modes are effective, how can they be
converted or transduced into the form of measurable signals, and how can
these signals be used to effect a target system, that is, mimic at least
some of the effector functions of the molecule in a target system?

[0004]These questions were addressed in recently filed co-owned patent
application Nos. 60/593,006 and 60/591,549 (attorney docket numbers
38547-8010 and -8011). Experiments conducted in support of the invention
described in the application demonstrate that certain effector functions
on a target system (in this case, one of a number of biological systems),
can be duplicated by exposing the target system to electromagnetic waves
produced by "transducing" a time-domain signal of the effector compound.
According to the earlier-described invention, the time-domain signal is
produced by recording a signal produced by the compound in a shielded
environment, while injecting a Gaussian white noise stimulus into the
recording apparatus at a level that enhances the ability to observe
low-frequency stochastic events produced by the compound. In the
earlier-described application, the transducing signal was the actual
compound time-domain signal of the effector compound.

[0005]The possibility of achieving effector-molecule functions by exposing
a target system to characteristic effector-molecule signals, without the
need for the actual presence of the effector agent, has a number of
important and intriguing applications. Instead of treating an organism by
the application of a drug, the same effect may be achieved by exposing
the organism to drug-specific signals. In the field of nanofabrication,
it might now be possible to catalyze or encourage self-assembly patterns
by introducing in the assembly system, signals characteristic of
multivalent effector molecules capable of promoting the desired pattern
of self-assembly.

[0006]It would be desirable, therefore, to employ systematic methods for
producing and selecting low-frequency time domain signals that are
effective, in a magnetic transduction environment, of producing
agent-specific effects on a mammalian or in vitro system.

SUMMARY OF THE INVENTION

[0007]The invention includes, in one aspect, a method for generating a
signal capable of producing an agent-specific effect on a mammalian
system, when the system is transduced by the signal within the
environment of an electromagnetic tranducer. The method includes the
steps of:

[0008](a) placing a sample containing the agent in a sample container
having both magnetic and electromagnetic shielding, where the sample acts
as a signal source for low-frequency molecular signals, and where the
magnetic shielding is external to a cryogenic container;

[0009](b) injecting a stimulus magnetic field into the sample, under a
selected stimulus magnetic-field condition,

[0010](c) recording a low-frequency, time-domain signal composed of sample
source radiation superimposed on the injected stimulus magnetic field in
the cryogenic container,

[0011](d) repeating steps (b) and (c) at each of a plurality of different
stimulus magnetic field conditions,

[0012](e) identifying from among the signals recorded in step (c), one or
more signals having the highest signal scores when analyzed by a scoring
algorithm that measures the number of low-frequency components above a
given threshold in a recorded signal,

[0013](f) testing each signal identified in step (e) for its ability to
produce an agent-specific response in a in vitro system containing
components that are responsive to the agent, when the in vitro system is
transduced with the signal within the environment of an electromagnetic
tranducer, and

[0014](g) selecting one or more signals that produce the greatest
agent-specific transduction effect in the in vitro system.

[0015]The different conditions of stimulus magnetic field may include (i)
white noise, injected at a voltage level calculated to produce a selected
magnetic field at the sample of between 0 and 1 G (Gauss), (ii) a DC
offset, injected at a voltage level calculated to produce a selected
magnetic field at the sample of between 0 and 1 G, and (iii) sweeps over
a low-frequency range, injected successively over a sweep range between
at least about 0-1 kHz, and at an injected voltage calculated to produce
a selected magnetic field at the sample of between 0 and 1 G.

[0016]Step (f) in the method may further include, after testing a
time-domain signal for its ability to produce an agent-specific response
in a in vitro system containing components that are responsive to the
agent, testing the ability of signal to produce an agent-specific
response under varying transduction conditions, including variations in
transduction voltage applied within the environment of an electromagnetic
tranducer, thus to optimize transduction conditions for transduction in
the mammalian system.

[0017]The step of identifying from among the recorded signals, one or more
signals having the highest signal scores, may be carried out by one of
the following algorithmic scoring methods:

[0018](i) autocorrelating the time domain signal, generating an FFT (Fast
Fourier Transform) of the autocorrelated signal over a selected frequency
range within the range DC to 8 kHz, assigning to the FFT signal a score
related to a number of peaks above a mean average noise value, and
selecting a time-domain signal based on the score;

[0019](ii) calculating a pair of phase spaces for two time domain signals,
and performing a mathematical comparison to provide a measure of
difference between the two;

[0020](iii) generating a histogram that shows, for each event bin f over a
selected frequency range within a range DC to 8 kHz, a number of event
counts in each bin, where f is a sampling rate for sampling the time
domain signal, assigning to the histogram, a score related to number of
bins that are above a given threshold; and selecting a time-domain signal
based on the score;

[0021](iv) cross-correlating a small block of data near the beginning of
the time domain signal with the remainder of the time series, and
counting the occurrences that the resulting cross-correlation surpasses a
given threshold; and

[0022](v) calculating a series of Fourier spectra of the time-domain
signal over each of multiple defined time periods, in a selected
frequency range between DC and 8 kHz, averaging the Fourier spectra;
assigning to the averaged FFT signal a score related to the number of
peaks above a mean average noise value, and selecting a time-domain
signal based on the score.

[0023]The electromagnetic transducer employed in the method may include a
Helmholtz coil having a pair of aligned electromagnetic coils defining a
sample magnetic environment therebetween, and the step of testing each
signal identified for its ability to produce an agent-specific response
in an in vitro system may include placing the in vitro system within the
aligned coils, and transducing the system with an agent-specific
time-domain signal identified in step (e).

[0024]Where the agent is an anti-neoplastic drug effective to promote
tubulin aggregation in vitro, step (f) of the method may include placing
a tubulin-containing composition within the environment of the
electromagnetic transducer, and transducing the composition with an
agent-specific time-domain signal identified in step (e).

[0025]In another aspect, the invention includes a method for generating
signals capable of producing an agent-specific effect on a in vitro or
mammalian system when the system is transduced by the signal within the
environment of an electromagnetic transducer. The method includes the
steps of:

[0026](a) placing a sample containing the agent in a sample container
having both magnetic and electromagnetic shielding, wherein the sample
acts as a signal source for molecular signals, and wherein the magnetic
shielding is external to a cryogenic container;

[0027](b) injecting a stimulus magnetic field into the sample, a under
selected stimulus magnetic field condition selected from the group
consisting of (i) white noise, injected at a voltage level calculated to
produce a selected magnetic field at the sample of between 0 and 1 G
(Gauss), (ii) a DC offset, injected at a voltage level calculated to
produce a selected magnetic field at the sample of between 0 and 1 G, and
(iii) sweeps over a low-frequency range, injected successively over a
sweep range between at least about 0-1 kHz, and at an injected voltage
calculated to produce a selected magnetic field at the sample of between
0 and 1 G.

[0028](c) recording a low-frequency, time-domain signal composed of sample
source radiation superimposed on the injected stimulus magnetic field in
the cryogenic container,

[0029](d) repeating steps (b) and (c) at each of a plurality of different
stimulus magnetic field conditions,

[0030](e) identifying from among the signals recorded in step (c), one or
more signals having the highest signal scores when analyzed by a scoring
algorithm that measures the number of low-frequency components above a
given threshold in a recorded signal, and

[0031](f) transducing the in vitro or mammalian system by placing the
system within the environment of an electromagnetic transducer, and
transducing the sample with a signal identified in step (e).

[0032]Step (e) of the method may be carried out, for example, by
autocorrelating the time domain signal, generating an FFT (Fast Fourier
Transform) of the autocorrelated signal over a selected frequency range
within the range DC to 8 kHz, assigning to the FFT signal a score related
to a number of peaks above a mean average noise value, and selecting a
time-domain signal based on the score;

[0033]The electromagnetic transducer employed in the method may include a
Helmholtz coil having a pair of aligned electromagnetic coils defining an
exposure station therebetween, constituting the environment of the
electromagnetic environment, and step (f) of the method may include
placing the chemical or in vitro system within the aligned coils, and
transducing the system with an agent-specific time-domain signal
identified in step (e).

[0034]Where the agent is an anti-neoplastic drug effective to promote
tubulin aggregation in the in vitro system, step (f) may include includes
placing a tubulin-containing composition within the environment of the
electromagnetic transducer, and transducing the composition with an
agent-specific, time-domain signal identified in step (e) under
conditions effective to produce signal-dependent aggregation of the
tubulin in the composition.

[0035]In still another embodiment, the invention includes apparatus for
producing low-frequency, time-domain signals that are candidates for
transducing a in vitro or mammalian system that is responsive to the
presence of a selected agent. The apparatus includes:

[0036](a) a sample container adapted for receiving a sample of an agent,
the container having both magnetic and electromagnetic shielding, where
the sample acts as a signal source for molecular signals, and where the
magnetic shielding is external to a cryogenic container;

[0037](b) an adjustable-power source operable to inject a stimulus
magnetic field into the container, with a sample in the container, at
each of a plurality of selected stimulus magnetic field conditions
selected from the group consisting of (i) white noise, injected at a
voltage level calculated to produce a selected magnetic field at the
sample of between 0 and 1 G (Gauss), (ii) a DC offset, injected at a
voltage level calculated to produce a selected magnetic field at the
sample of between 0 and 1 G, and (iii) sweeps over a low-frequency range,
injected successively over a sweep range between at least about 0-1 kHz,
and at an injected voltage calculated to produce a selected magnetic
field at the sample of between 0 and 1 G.

[0038](c) a detector for recording, at each of the different stimulus
magnetic field conditions injected by said power source, (b) the
electromagnetic time-domain signals composed of sample source radiation
superimposed on the injected stimulus magnetic fields,

[0039](d) a memory device for storing the signals recorded by the
detector, and

[0040](e) a computer operable to:

[0041](i) retrieve time-domain signals stored in the memory device;

[0042](ii) analyzing the retrieved time-domain signals by a scoring
algorithm that measures the number of low-frequency components above a
given threshold in a recorded signal, and

[0043](iii) identifying those time-domain signals having the greatest
number of low-frequency components above the threshold.

[0044]The sample container may be an attenuation tube having a
sample-holding region, a magnetic shielding cage surrounding the region,
and a Faraday cage contained within the magnetic shielding cage and also
surrounding the region, the source of a Gaussian noise includes a
Gaussian noise generator and a Helmholtz coil which is contained within
the magnetic cage and the Faraday cage, and which receives a noise output
signal from the noise generator, and which further includes, for use in
removing stationary noise components in the time-dependent signal, a
signal inverter operatively connected to the noise source and to the
SQUID (Superconducting QUantum Interference Device), for receiving
Gaussian noise from the noise source and outputting into the SQUID,
Gaussian noise in inverted form with respect to the Gaussian noise
injected into the sample.

[0045]The power source may be operable to inject an offset voltage into
the container, with a sample in the container, at each of a plurality of
selected offset voltages calculated to produce a selected magnetic field
at the sample of between 0 and 1 G (Gauss). Alternatively, the power
source may be operable to inject generate successive sweeps over a
sweep-frequency range between at least about 0 and 1 kHz, at each of a
plurality of different sweep voltages calculated to produce a selected
magnetic field at the sample of between 0 and 1 G (Gauss).

[0046]The computer in the apparatus may be operable, in analyzing the
retrieved time-domain signals is operable to apply an analysis algorithm
selected from one of:

[0047](i) autocorrelating the time domain signal, generating an FFT (Fast
Fourier Transform) of the autocorrelated signal over a selected frequency
range within the range DC to 8 kHz, assigning to the FFT signal a score
related to a number of peaks above a mean average noise value, and
selecting a time-domain signal based on the score;

[0048](ii) calculating a pair of phase spaces for two time domain signals,
and performing a mathematical comparison to provide a measure of
difference between the two;

[0049](iii) generating a histogram that shows, for each event bin f over a
selected frequency range within a range DC to 8 kHz, a number of event
counts in each bin, where f is a sampling rate for sampling the time
domain signal, assigning to the histogram, a score related to number of
bins that are above a given threshold; and selecting a time-domain signal
based on the score;

[0050](iv) cross-correlating a small block of data near the beginning of
the time domain signal with the remainder of the time series, and
counting the occurrences that the resulting cross-correlation surpasses a
given threshold; and

[0051](v) calculating a series of Fourier spectra of the time-domain
signal over each of multiple defined time periods, in a selected
frequency range between DC and 8 kHz, averaging the Fourier spectra;
assigning to the averaged FFT signal a score related to the number of
peaks above a mean average noise value, and selecting a time-domain
signal based on the score.

[0052]Also disclosed is a system for producing an agent-specific effect on
a mammalian system. The system includes:

[0053](1) a storage medium having stored thereon, an agent-specific
low-frequency time-domain signal produced by the steps of:

[0054](a) placing a sample to which the mammalian system is responsive in
a sample container having both magnetic and electromagnetic shielding,
wherein the sample acts as a signal source for low-frequency molecular
signals, and wherein the magnetic shielding is external to a cryogenic
container;

[0055](b) injecting a stimulus magnetic field into the sample, under a
selected stimulus magnetic field condition,

[0056](c) recording a low-frequency, time-domain signal composed of sample
source radiation superimposed on the injected stimulus magnetic field in
the cryogenic container,

[0057](d) repeating steps (b) and (c) at each of a plurality of different
stimulus magnetic field conditions,

[0058](e) identifying from among the signals recorded in step (c), one or
more signals having the highest signal scores when analyzed by a scoring
algorithm that measures the number of low-frequency components above a
given threshold in a recorded signal,

[0059](f) testing each signal identified in step (e) for its ability to
produce an agent-specific response in an in vitro in vitro system
containing components that are responsive to the agent, when the in vitro
system is transduced by the signal within the environment of an
electromagnetic transducer,

[0060](2) an electromagnetic transducer composed of one or more
electromagnetic coils, said coils having an interior region defining a
magnetic environment in which the sample is received, and

[0061](3) an amplifier for amplifying a signal from the storage medium and
supplying the amplified signal to the transduction coil(s).

[0062]The electromagnetic transducer may include a Helmholtz coil having a
pair of aligned electromagnetic coils defining an interior region
therebetween.

[0063]In yet another embodiment, the invention includes a storage medium
having stored thereon, an agent-specific low-frequency time-domain signal
produced by the steps of:

[0064](a) placing a sample to which the mammalian system is responsive in
a sample container having both magnetic and electromagnetic shielding,
wherein the sample acts as a signal source for low-frequency molecular
signals, and wherein the magnetic shielding is external to a cryogenic
container;

[0065](b) injecting a stimulus magnetic field into the sample, under a
selected stimulus magnetic field condition,

[0066](c) recording a low-frequency, time-domain signal composed of sample
source radiation superimposed on the injected stimulus magnetic field in
the cryogenic container,

[0067](d) repeating steps (b) and (c) at each of a plurality of different
stimulus magnetic field conditions,

[0068](e) identifying from among the signals recorded in step (c), one or
more signals having the highest signal scores when analyzed by a scoring
algorithm that measures the number of low-frequency components above a
given threshold in a recorded signal,

[0069](f) testing each signal identified in step (e) for its ability to
produce an agent-specific response in an in vitro in vitro system
containing components that are responsive to the agent, when the in vitro
system is transduced by the signal within the environment of an
electromagnetic transducer.

[0070]The signal carried on the storage medium may be produced, for
example, by an anti-neoplastic agent effective to promote tubulin
aggregation in vitro.

[0071]These and other objects and features of the invention will be more
fully understood when the following detailed description of the invention
is read in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0072]FIG. 1 is an isometric view of one embodiment of a molecular
electromagnetic signaling detection apparatus formed in accordance with
one embodiment of the present invention;

[0073]FIG. 2 is an enlarged, detail view of the faraday cage and its
contents shown in FIG. 1;

[0074]FIG. 3 is an enlarged, cross sectional view of one of the
attenuation tubes shown in FIGS. 1 and 2.

[0075]FIG. 4 is a cross-section view of the faraday cage and its contents
shown in FIG. 2.

[0076]FIG. 5 is a diagram of an alternative electromagnetic emission
detection system.

[0077]FIG. 6 diagram of the processing unit included in the detection
system of the above figures.

[0078]FIG. 7 is a diagram of an alternative processing unit to that of
FIG. 6.

[0079]FIG. 8 is a flow diagram of the signal detection and processing
performed by the present system.

[0080]FIG. 9 shows a high-level flow diagram of data flow for the
histogram spectral plot method of the invention;

[0081]FIG. 10 is a flow diagram of the algorithm for generating a spectral
plot histogram, in accordance with the invention,

[0082]FIG. 11 is a flow diagram of steps in identify optimal time-domain
signals in accordance with a second embodiment of the method of the
invention;

[0083]FIG. 12 is a flow diagram of steps to identify optimal time-domain
signals in accordance with a third embodiment of the method of the
invention;

[0084]FIG. 13 shows an example signal Score result, where the upper graph
shows File # on the X-axis, Tau on the Y-axis, and Score on the Z-axis.

[0086]FIG. 15 shows a transduction coil and container used in a typical
transduction experiment.

[0087]FIGS. 16A-16F are bar-graphs of the rate of tubulin polymerization
measured at OD, calculated at 1, 2, 3, 4, and 5, minutes, respectively,
after addition of taxol or initiation of a transduction signal;

[0088]FIG. 17 is a bar graph showing Vmax values for the tubulin assay of
FIG. 16, calculated at the end of a 20-minute assay reaction; and

[0089]FIG. 18 shows survival time in days, for mice injected
intracranially with glioblastoma cells, and after transduction with a
taxol time-domain signal.

DETAILED DESCRIPTION OF THE INVENTION

I. Definitions

[0090]The terms below have the following definitions unless indicated
otherwise.

[0091]"Magnetic shielding" refers to shielding that decreases, inhibits or
prevents passage of magnetic flux as a result of the magnetic
permeability of the shielding material.

[0093]"Time-domain signal" or "time-series signal" refers to a signal with
transient signal properties that change over time.

[0094]"Sample-source radiation" or refers to magnetic flux or
electromagnetic flux emissions resulting from molecular motion of a
sample, such as the rotation of a molecular dipole in a magnetic field.
Because sample source radiation is produced in the presence of an
injected magnetic-field stimulus," it is also referred to as "sample
source radition superimposed on injected magnetic field stimulus."

[0095]"Stimulus magnetic field" or "Magnetic-field stimulus" refers to a
magnetic field produced by injecting (applying) to magnetic coils
surrounding a sample, one of a number of electromagnetic signals that may
include (i) white noise, injected at voltage level calculated to produce
a selected magnetic field at the sample of between 0 and 1 G (Gauss),
(ii) a DC offset, injected at voltage level calculated to produce a
selected magnetic field at the sample of between 0 and 1 G, and (iii)
sweeps over a low-frequency range, injected successively over a sweep
range between at least about 0-1 kHz, and at an injected voltage
calculated to produce a selected magnetic field at the sample of between
0 and 1 G. The magnetic field produced at the sample may be readily
calculated using known electromagnetic relationships, knowing the shape
and number of windings in the injection coil, the voltage applied to
coils, and the distance between the injection coils and the sample.

[0097]"White noise" means random noise or a signal having simultaneous
multiple frequencies, e.g. white random noise or deterministic noise.
"Gaussian white noise" means white noise having a Gaussian power
distribution. "Stationary Gaussian white noise" means random Gaussian
white noise that has no predictable future components. "Structured noise"
is white noise that may contain a logarithmic characteristic which shifts
energy from one region of the spectrum to another, or it may be designed
to provide a random time element while the amplitude remains constant.
These two represent pink and uniform noise, as compared to truly random
noise which has no predictable future component. "Uniform noise" means
white noise having a rectangular distribution rather than a Gaussian
distribution.

[0098]"Frequency-domain spectrum" refers to a Fourier frequency plot of a
time-domain signal.

[0099]"Spectral components" refer to singular or repeating qualities
within a time-domain signal that can be measured in the frequency,
amplitude, and/or phase domains. Spectral components will typically refer
to signals present in the frequency domain.

[0101]A "signal-analysis score" refers to a score based on the number
and/or amplitude of agent-specific spectral peaks observed over a
selected low-frequency range, e.g., DC to 1 kHz or DC to 8 kHz, in a
time-domain signal recorded for an agent or sample that has been
processed by a suitable method, such as one of the five methods described
herein, to reveal identifiable spectral features that are specific to the
agent or sample.

[0103]"In vitro system" refers to a biochemical system having of one or
more biochemical components, such as nucleic acid or protein components,
including receptors and structural proteins isolated or derived from a
virus, bacteria, or multicellular plant or animal. An in vitro system
typically is a solution or suspension of one or more isolated or
partially isolated in vitro components in an aqueous medium, such as a
physiological buffer. The term also refers to a cell culture system
containing bacterial or eukaryotic cells in a culture medium.

[0104]"Mammalian system" refers to a mammal, include a laboratory animal
such as mouse, rat, or primate that may serve as a model for a human
disease, or a human patient.

[0105]"Agent-specific effect" refers to an effect observed when an in
vitro or mammalian system is exposed to an agent (effector). Examples of
agent-specific in vitro effects include, for example, a change in the
state of aggregation of components of the system, the binding the an
agent to a target, such as a receptor, and the change in growth or
division of cells in culture.

II. Recording Apparatus and Method

[0106]The following description of a signal recording devices in
accordance with the invention provides specific details for a thorough
understanding of, and enabling description for, embodiments of the
invention. However, one skilled in the art will understand that the
invention may be practiced without these details. In other instances,
well-known structures and functions have not been shown or described in
detail to avoid unnecessarily obscuring the description of embodiments of
the invention.

[0107]As explained in detail below, embodiments of the present invention
are directed to providing an apparatus and method for the repeatable
detection and recording of low-threshold molecular electromagnetic
signals for later, remote use. A magnetically shielded faraday cage
shields the sample material and detection apparatus from extraneous
electromagnetic signals. Within the magnetically shielded faraday cage, a
coil injects a stimulus signal such as Gaussian white noise, a
non-ferrous tray holds the sample, and a gradiometer detects
low-threshold molecular electromagnetic response signals. The apparatus
further includes a superconducting quantum interference device ("SQUID")
and a preamplifier.

[0108]The apparatus is used by placing a sample within the magnetically
shielded faraday cage in close proximity to the coil that generates the
stimulus signal and the gradiometer that measures the response. A
stimulus signal is injected through the stimulus coil and modulated until
the molecular electromagnetic signal is optimized. The molecular
electromagnetic response signal, shielded from external interference by
the faraday cage and the field generated by the stimulus coil, is then
detected and measured by the gradiometer and SQUID. The signal is then
amplified and transmitted to any appropriate recording or measuring
equipment.

[0109]Referring to FIGS. 1 and 2, there is shown a shielding structure 10,
in the form of a Faraday cage, which includes, in an outer to inner
direction, a conductive wire cage 16 which is a magnetic shield and inner
conductive wire cages 18 and 20 which provide electromagnetic shielding.
In another embodiment, the outer magnetic shield is formed of a solid
aluminum plate material having an aluminum-nickel alloy coating, and the
electromagnetic shielding is provided by two inner wall structures, each
formed of solid aluminum.

[0110]The faraday cage 10 is open at the top, and includes side openings
12 and 14. The faraday cage 10 is further comprised of three copper mesh
cages 16, 18 and 20, nestled in one another. Each of the copper mesh
cages 16, 18 and 20 is electrically isolated from the other cages by
dielectric barriers (not shown) between each cage.

[0111]Side openings 12 and 14 further comprise attenuation tubes 22 and 24
to provide access to the interior of the faraday cage 10 while isolating
the interior of the cage from external sources of interference. Referring
to FIG. 3, attenuation tube 24 is comprised of three copper mesh tubes
26, 28 and 30 (FIG. 3), nestled in one another. The exterior copper mesh
cages 16, 18 and 20 are each electrically connected to one of the copper
mesh tubes 26, 28 and 30, respectively. Attenuation tube 24 is further
capped with cap 32, with the cap having hole 34. Attenuation tube 22 is
similarly comprised of copper mesh tubes 26, 28 and 30, but does not
include cap 32.

[0112]Referring again to FIG. 2, a low-density nonferrous sample tray 50
is mounted in the interior of the faraday cage 10. The sample tray 50 is
mounted so that it may be removed from the faraday cage 10 through the
attenuation tube 22 and side opening 12. Three rods 52, each of which is
greater in length than the distance from the center vertical axis of the
faraday cage 10 to the outermost edge of the attenuation tube 22, are
attached to the sample tray 50. The three rods 52 are adapted to conform
to the interior curve of the attenuation tube 22, so that the sample tray
50 may be positioned in the center of the faraday cage 10 by resting the
rods in the attenuation tube. In the illustrated embodiment, the sample
tray 50 and rods 52 are made of glass fiber epoxy. It will be readily
apparent to those skilled in the art that the sample tray 50 and rods 52
may be made of other nonferrous materials, and the tray may be mounted in
the faraday cage 10 by other means, such as by a single rod.

[0113]Referring again to FIG. 2, mounted within the Faraday cage 10 and
above the sample tray 50 is a cryogenic dewar 100. In the disclosed
embodiment, the dewar 100 is adapted to fit within the opening at the top
of faraday cage 10 and is a Model BMD-6 Liquid Helium Dewar manufactured
by Tristan Technologies, Inc. The dewar 100 is constructed of a
glass-fiber epoxy composite. A gradiometer 110 with a very narrow field
of view is mounted within the dewar 100 in position so that its field of
view encompasses the sample tray 50. In the illustrated embodiment, the
gradiometer 110 is a first order axial detection coil, nominally 1
centimeter in diameter, with a 2% balance, and is formed from a
superconductor. The gradiometer can be any form of gradiometer excluding
a planar gradiometer. The gradiometer 110 is connected to the input coil
of one low temperature direct current superconducting quantum
interference device ("SQUID") 120. In the disclosed embodiment, the SQUID
is a Model LSQ/20 LTS dc SQUID manufactured by Quantum Design, Inc. It
will be recognized by those skilled in the art that high temperature or
alternating current SQUIDs can be used without departing from the spirit
and scope of the invention. In an alternative embodiment, the SQUID 120
includes a noise suppression coil 124.

[0114]The disclosed combination of gradiometer 110 and SQUID 120 have a
sensitivity of 5 microTesla/ Hz when measuring magnetic fields.

[0115]The output of SQUID 120 is connected to a Model SP Cryogenic Cable
130 manufactured by Tristan Technologies, Inc. The Cryogenic Cable 130 is
capable of withstanding the temperatures within and without the dewar 100
and transfers the signal from the SQUID 120 to Flux-Locked Loop 140,
which is mounted externally to the faraday cage 10 and dewar 100. The
Flux-Locked Loop 140 in the disclosed embodiment is an iFL-301-L Flux
Locked Loop manufactured by Tristan Technologies, Inc.

[0116]Referring to FIG. 1, the Flux Locked Loop 140 further amplifies and
outputs the signal received from the SQUID 120 via high-level output
circuit 142 to an iMC-303 iMAG® SQUID controller 150. The Flux-Locked
Loop 140 is also connected via a model CC-60 six-meter fiber-optic
composite connecting cable 144 to the SQUID controller 150. The
fiber-optic connecting cable 144 and SQUID controller 150 are
manufactured by Tristan Technologies, Inc. The controller 150 is mounted
externally to the magnetic shielding cage 40. The fiber-optic connecting
cable 144 carriers control signals from the SQUID controller 150 to the
Flux Locked Loop 140, further reducing the possibility of electromagnetic
interference with the signal to be measured. It will be apparent to those
skilled in the art that other Flux-Locked Loops, connecting cables, and
SQUID controllers can be used without departing from the spirit and scope
of the invention.

[0118]Referring to FIGS. 2 and 4 a two-element Helmholtz transformer 60 is
installed to either side of the sample tray 50 when the sample tray is
fully inserted within the faraday cage 10. In the illustrated embodiment,
the coil windings 62 and 64 of the Helmholtz transformer 60 are designed
to operate in the direct current to 50 kilohertz range, with a center
frequency of 25 kilohertz and self-resonant frequency of 8.8 megahertz.
In the illustrated embodiment, the coil windings 62 and 64 are generally
rectangular in shape and are approximately 8 inches tall by 4 inches
wide. Other Helmholtz coil shapes may be used but should be shaped and
sized so that the gradiometer 110 and sample tray 50 are positioned
within the field produced by the Helmholtz coil. Each of coil windings 62
and 64 is mounted on one of two low-density nonferrous frames 66 and 68.
The frames 66 and 68 are hingedly connected to one another and are
supported by legs 70. Frames 66 and 68 are slidably attached to legs 70
to permit vertical movement of the frames in relation to the lower
portion of dewar 100. Movement of the frames permits adjustment of the
coil windings 62 and 64 of the Helmholtz transformer 60 to vary the
amplitude of the magnetic-field stimulus, e.g., Gaussian white noise
received at gradiometer 110. The legs 70 rest on or are epoxied onto the
bottom of the faraday cage 10. In the illustrated embodiment, the frames
66 and 68 and legs 70 are made of glass fiber epoxy. Other arrangements
of transformers or coils may be used around the sample tray 50 without
departing from the spirit and scope of the invention.

[0119]Referring to FIG. 4, there is shown a cross-sectional view of the
faraday cage and its contents, showing windings 62 of Helmholtz
transformer 60 in relation to dewar 100 and faraday cage 10. Note also in
FIG. 4 the positioning of sample tray 50 and sample 200.

[0120]Referring again to FIG. 1, an amplitude adjustable Gaussian white
noise stimulus generator 80 is external to magnetic shielding cage 40,
and is electrically connected to the Helmholtz transformer 60 through
filter 90 by electrical cable 82. As will be discussed below, sources of
magnetic-field stimulus injected into the sample during signal recording
other than a Gaussian noise generator may be employed. It will therefore
be recognized in the description that follows that the Gaussian generator
is simply exemplary of a source of magnetic-field stimulus that is
injected into the recording system during signal recording.

[0121]Referring to FIG. 3, cable 82 is run through side opening 12,
attenuation tube 24, and through cap 32 via hole 34. Cable 82 is a
co-axial cable further comprising a twisted pair of copper conductors 84
surrounded by interior and exterior magnetic shielding 86 and 88,
respectively. In other embodiments, the conductors can be any nonmagnetic
electrically conductive material, such as silver or gold. The interior
and exterior magnetic shielding 86 and 88 terminates at cap 32, leaving
the twisted pair 84 to span the remaining distance from the end cap to
the Helmholtz transformer 60 shown in FIG. 1. The interior magnetic
shielding 86 is electrically connected to Faraday cage 16 through cap 32,
while the exterior magnetic shielding is electrically connected to the
magnetically shielded cage 40 shown in FIG. 1.

[0122]Referring to FIG. 1, the Gaussian white noise stimulus generator 80
can generate a nearly flat frequency spectrum from zero to 100 kilohertz,
and at a selected voltage amplitude, e.g., between 0.01 to 1.0 volts,
that produces a selected calculated magnetic field at the same of between
0-1 G (Gauss), e.g., over increments of 25 mG. In the illustrated
embodiment, the filter 90 filters out noise above 50 kilohertz, but other
frequency ranges may be used without departing from the spirit and scope
of the invention.

[0123]The Gaussian white noise stimulus may be replaced by other stimulus
signal patterns. Examples of such patterns include scanning a range of
sine wave frequencies, a square wave, time-series data containing defined
non-linear structure, or the SQUID output itself. These signals may
themselves be pulsed between off and on states to further modify the
stimulus signal. The white noise naturally generated by the magnetic
shields may also be used as the source of the stimulus signal. In one
embodiment, the source of a magnetic-field stimulus is simply a
adjustable-voltage DC source that is operated to supply a DC voltage
(offset) to the magnetic-stimulus coils, as a selected voltage, e.g.,
0.01 to 1.0 volts, that produces a calculated magnetic field at the
sample between 0 and 1 G (gauss). In still another embodiment, the source
of the magnetic-field stimulus is a frequency-sweep generator that is
operator to produce successive, sweeps over a selected frequency of
preferably at least 0 to 1 kH, and typically 0 to 10 kHz or higher. The
sweep time is preferably 1 to 10 seconds, and at a selected voltage
level, e.g., between 0.01 to 1.0 volts, that produces a selected
calculated magnetic field at the sample of between 0 and 1 G. Thus the
sweep generator might be set to produce successive frequency sweep every
five seconds, over a sweep frequency between 1 to 10 Khz, and a selected
voltage level.

[0124]While not intending to be bound by a particular mechanism or model
of signal generation, it appears that the injected magnetic-field
stimulus is acting to stimulate or amplify certain low-frequency events
or modes in the sample, such that the recorded time-domain signal is
composed of these events superimposed on the signal background. Where the
injected magnetic-field stimulus is white noise, the mechanism of
stimulus may involve stochastic resonance. Where the magnetic-field
stimulus is a DC offset, the stimulus may function to stimulate a nuclear
or electron resonance process, in which case the recorded signal would
have NMR or ESR components. Where the magnetic-field stimulus is a sweep
frequency generator, the stimulus may serve to excite those low-frequency
events corresponding to the instantaneous frequencies seen by the sample.

[0125]Gaussian white noise stimulus generator 80 is also electrically
connected to the other input of dual trace oscilloscope 160 through patch
cord 164.

[0126]Referring to FIGS. 1, 2 and 3, a sample of the substance 200 to be
measured is placed on the sample tray 50 and the sample tray is placed
within the faraday cage 10. In the first embodiment, the Gaussian white
noise stimulus generator 80 is used to inject Gaussian white noise
stimulus through the Helmholtz transformer 60. The noise signal creates
an induced voltage in the gradiometer 110. The induced voltage in the
gradiometer 110 is then detected and amplified by the SQUID 120, the
output from the SQUID is further amplified by the flux locked loop 140
and sent to the SQUID controller 150, and then sent to the dual trace
oscilloscope 160. The dual trace oscilloscope 160 is also used to display
the signal generated by Gaussian white noise stimulus generator 80.

[0127]The Gaussian white noise stimulus signal (or other magnetic-field
stimulus) is adjusted by altering the output of the stimulus generator 80
and by rotating the Helmholtz transformer 60 around the sample 200, shown
in FIG. 2. Rotation of the Helmholtz transformer 60 about the axis of the
hinged connection of frames 66 and 68 alters its phasing with respect to
the gradiometer 110. Depending upon the desired phase alteration, the
hinged connection of frames 66 and 68 permits windings 62 and 64 to
remain parallel to one another while rotating approximately 30 to 40
degrees around sample tray 50. The hinged connection also permits
windings 62 and 64 to rotate as much as approximately 60 degrees out of
parallel, in order to alter signal phasing of the field generated by
Helmholtz transformer 60 with respect to gradiometer 110. The typical
adjustment of phase will include this out-of-parallel orientation,
although the other orientation may be preferred in certain circumstances,
to accommodate an irregularly shaped sample 200, for example. Stimulus is
applied at a selected stimulus "condition," that is, selected voltage
when applying white noise or a DC offset, and a selected sweep frequency
range, a repeat period, and a voltage level for a sweep stimulus.

[0128]Embodiments of the present invention provide a method and apparatus
for detecting extremely low-threshold molecular electromagnetic signals
without external interference. They further provide for the output of
those signals in a format readily usable by a wide variety of signal
recording and processing equipment.

[0129]Referring now to FIG. 5, an alternative embodiment to the molecular
electromagnetic emission detection and processing system of the above
figures is shown. A system 700 includes a detection unit 702 coupled to a
processing unit 704. Although the processing unit 704 is shown external
to the detection unit 702, at least a part of the processing unit can be
located within the detection unit.

[0130]The detection unit 702, which is shown in a cross-sectional view in
FIG. 5, includes multiple components nested or concentric with each
other. A sample chamber or faraday cage 706 is nested within a metal cage
708. Each of the sample chamber 706 and the metal cage 708 can be
comprised of aluminum material. The sample chamber 706 can be maintained
in a vacuum and may be temperature controlled to a preset temperature.
The metal cage 708 is configured to function as a low pass filter.

[0131]Between the sample chamber 706 and the metal cage 708 and encircling
the sample chamber 706 are a set of parallel heating coils or elements
710. One or more temperature sensor 711 is also located proximate to the
heating elements 710 and the sample chamber 706. For example, four
temperature sensors may be positioned at different locations around the
exterior of the sample chamber 706. The heating elements 710 and the
temperature sensor(s) 711 may be configured to maintain a certain
temperature inside the sample chamber 706.

[0132]A shield 712 encircles the metal cage 708. The shield 712 is
configured to provide additional magnetic field shielding or isolation
for the sample chamber 706. The shield 712 can be comprised of lead or
other magnetic shielding materials. The shield 712 is optional when
sufficient shielding is provided by the sample chamber 706 and/or the
metal cage 708.

[0133]Surrounding the shield 712 is a cryogen layer 716 with G10
insulation. The cryogen may be liquid helium. The cryogen layer 716 (also
referred to as a cryogenic Dewar) is at an operating temperature of 4
degrees Kelvin. Surrounding the cryogen layer 716 is an outer shield 718.
The outer shield 718 is comprised of nickel alloy and is configured to be
a magnetic shield. The total amount of magnetic shielding provided by the
detection unit 702 is approximately -100 dB, -100 dB, and -120 dB along
the three orthogonal planes of a Cartesian coordinate system.

[0134]The various elements described above are electrically isolated from
each other by air gaps or dielectric barriers (not shown). It should also
be understood that the elements are not shown to scale relative to each
other for ease of description.

[0135]A sample holder 720 can be manually or mechanically positioned
within the sample chamber 706. The sample holder 720 may be lowered,
raised, or removed from the top of the sample chamber 706. The sample
holder 72015 comprised of a material that will not introduce Eddy
currents and exhibits little or no inherent molecular rotation. As an
example, the sample holder 720 can be comprised of high quality glass or
Pyrex.

[0136]The detection unit 702 is configured to handle solid, liquid, or gas
samples. Various sample holders may be utilized in the detection unit
702. For example, depending on the size of the sample, a larger sample
holder may be utilized. As another example, when the sample is reactive
to air, the sample holder can be configured to encapsulate or form an
airtight seal around the sample. In still another example, when the
sample is in a gaseous state, the sample can be introduced inside the
sample chamber 706 without the sample holder 720. For such samples, the
sample chamber 706 is held at a vacuum. A vacuum seal 721 at the top of
the sample chamber 706 aids in maintaining a vacuum and/or accommodating
the sample holder 720.

[0137]A sense coil 722 and a sense coil 724, also referred to as detection
coils, are provided above and below the sample holder 720, respectively.
The coil windings of the sense coils 722, 724 are configured to operate
in the direct current (DC) to approximately 50 kilohertz (kHz) range,
with a center frequency of 25 kHz and a self-resonant frequency of 8.8
MHz. The sense coils 722, 724 are in the second derivative form and are
configured to achieve approximately 100% coupling. In one embodiment, the
coils 722, 724 are generally rectangular in shape and are held in place
by G10 fasteners. The coils 722, 724 function as a second derivative
gradiometer.

[0138]Helmholtz coils 726 and 728 may be vertically positioned between the
shield 712 and the metal cage 708, as explained herein. Each of the coils
726 and 728 may be raised or lowered independently of each other. The
coils 726 and 728, also referred to as magnetic-field stimulus generation
coils, are at room or ambient temperature. The noise generated by the
coils 726, 728 is approximately 0.10 Gauss.

[0139]The degree of coupling between the emissions from the sample and the
coils 722, 724 may be changed by repositioning the sample holder 720
relative to the coils 722, 724, or by repositioning one or both of the
coils 726, 728 relative to the sample holder 720.

[0140]The processing unit 704 is electrically coupled to the coils 722,
724, 726, and 728. The processing unit 704 specifies the magnetic-field
stimulus, e.g., Gaussian white noise stimulus to be injected by the coils
726, 728 to the sample. The processing unit 104 also receives the induced
voltage at the coils 722, 724 from the sample's electromagnetic emissions
mixed with the injected magnetic-field stimulus.

[0141]Referring to FIG. 6, a processing unit employing aspects of the
invention includes a sample tray 840 that permits a sample 842 to be
inserted into, and removed from, a Faraday cage 844 and Helmholtz coil
746. A SQUID/gradiometer detector assembly 848 is positioned within a
cryogenic dewar 850. A flux-locked loop 852 is coupled between the
SQUID/gradiometer detector assembly 848 and a SQUID controller 854. The
SQUID controller 854 may be a model iMC-303 iMAG multichannel controller
provided by Tristan Technologies, Inc.

[0142]An analog Gaussian white noise stimulus generator 856 provides a
noise signal (as noted above) to a phase lock loop 858. The x-axis output
of the phase lock loop is provided to the Helmholtz coil 846, and may be
attenuated, such as by 20 dB. The y-axis output of the phase lock loop is
split by a signal splitter 860. One portion of the y-axis output is input
to the noise cancellation coil at the SQUID, which has a separate input
for the gradiometer. The other portion of the y-axis signal is input
oscilloscope 862, such as an analog/digital oscilloscope having Fourier
functions like the Tektronix TDS 3000b (e.g., model 3032b). That is, the
x-axis output of the phase lock loop drives the Helmholtz coil, and the
y-axis output, which is in inverted form, is split to input the SQUID and
the oscilloscope. Thus, the phase lock loop functions as a signal
inverter. The oscilloscope trace is used to monitor the analog
magnetic-field stimulus signal. An analog tape recorder or recording
device 864, coupled to the controller 854, records signals output from
the device, and is preferably a wideband (e.g. 50 kHz) recorder. A PC
controller 866 may be an MS Windows based PC interfacing with the
controller 854 via, for example, an RS 232 port.

[0143]In FIG. 7, a block diagram of another embodiment of the processing
unit is shown. A dual phase lock-in amplifier 202 is configured to
provide a first magnetic-field signal (e.g., "x" or noise stimulus
signal) to the coils 726, 728 and a second magnetic-field signal (e.g.,
"y" or noise cancellation signal) to a noise cancellation coil of a
superconducting quantum interference device (SQUID) 206. The amplifier
202 is configured to lock without an external reference and may be a
Perkins Elmer model 7265 DSP lock-in amplifier. This amplifier works in a
"virtual mode," where it locks to an initial reference frequency, and
then removes the reference frequency to allow it to run freely and lock
to "noise."

[0144]A magnetic-field stimulus generator, such as an analog Gaussian
white noise stimulus generator 200 is electrically coupled to the
amplifier 202. The generator 200 is configured to generate a selected
magnetic-field stimulus, e.g., analog Gaussian white noise stimulus at
the coils 726, 728 via the amplifier 202. As an example, the generator
200 may be a model 1380 manufactured by General Radio.

[0145]An impedance transformer 204 is electrically coupled between the
SQUID 206 and the amplifier 202. The impedance transformer 204 is
configured to provide impedance matching between the SQUID 206 and
amplifier 202.

[0146]The SQUID 206 is a low temperature direct element SQUID. As an
example, the SQUID 206 may be a model LSQ/20 LTS dC SQUID available form
Tristan Technologies, Inc (San Diego, Calif.) Alternatively, a high
temperature or alternating current SQUID can be used. The coils 722, 724
(e.g., gradiometer) and the SQUID 206 (collectively referred to as the
SQUID/gradiometer detector assembly) combined has a magnetic field
measuring sensitivity of approximately 5 microTesla/ Hz. The induced
voltage in the coils 722, 724 is detected and amplified by the SQUID 206.
The output of the SQUID 206 is a voltage approximately in the range of
0.2-0.8 microVolts.

[0147]The output of the SQUID 206 is the input to a SQUID controller 208.
The SQUID controller 208 is configured to control the operational state
of the SQUID 206 and further condition the detected signal. As an
example, the SQUID controller 208 may be an iMC-303 iMAG multi-channel
SQUID controller manufactured by Tristan Technologies, Inc.

[0148]The output of the SQUID controller 208 is inputted to an amplifier
210. The amplifier 210 is configured to provide a gain in the range of
0-100 dB. A gain of approximately 20 dB is provided when noise
cancellation node is turned on at the SQUID 206. A gain of approximately
50 dB is provided when the SQUID 206 is providing no noise cancellation.

[0149]The amplified signal is inputted to a recorder or storage device
212. The recorder 212 is configured to convert the analog amplified
signal to a digital signal and store the digital signal. In one
embodiment, the recorder 212 stores 8600 data points per Hz and can
handle 2.46 Mbits/sec. As an example, the recorder 212 may be a Sony
digital audiotape (DAT) recorder. Using a DAT recorder, the raw signals
or data sets can be sent to a third party for display or specific
processing as desired.

[0150]A lowpass filter 214 filters the digitized data set from the
recorder 212. The lowpass filter 214 is an analog filter and may be a
Butterworth filter. The cutoff frequency is at approximately 50 kHz.

[0151]A bandpass filter 216 next filters the filtered data sets. The
bandpass filter 216 is configured to be a digital filter with a bandwidth
between DC to 50 kHz. The bandpass filter 216 can be adjusted for
different bandwidths.

[0152]The output of the bandpass filter 216 is the input to a Fourier
transformer processor 218. The Fourier transform processor 218 is
configured to convert the data set, which is in the time domain, to a
data set in the frequency domain. The Fourier transform processor 218
performs a Fast Fourier Transform (FFT) type of transform.

[0153]The Fourier transformed data sets are the input to a correlation and
comparison processor 220. The output of the recorder 212 is also an input
to the processor 220. The processor 220 is configured to correlate the
data set with previously recorded data sets, determine thresholds, and
perform noise cancellation (when no noise cancellation is provided by the
SQUID 206). The output of the processor 220 is a final data set
representative of the spectrum of the sample's molecular low frequency
electromagnetic emissions.

[0154]A user interface (UI) 222, such as a graphical user interface (GUI),
may also be connected to at least the filter 216 and the processor 220 to
specify signal processing parameters. The filter 216, processor 218, and
the processor 220 can be implemented as hardware, software, or firmware.
For example, the filter 216 and the processor 218 may be implemented in
one or more semiconductor chips. The processor 220 may be software
implemented in a computing device.

[0155]This amplifier works in a "virtual mode," where it locks to an
initial reference frequency, and then removes the reference frequency to
allow it to run freely and lock to "noise." The analog noise generator
(which is produced by General Radio, a truly analog noise generator)
requires 20 dB and 45-dB attenuation for the Helmholtz and noise
cancellation coil, respectively.

[0156]The Helmholtz coil may have a sweet spot of about one cubic inch
with a balance of 1/100th of a percent. In an alternative
embodiments, the Helmholtz coil may move both vertically, rotationally
(about the vertical axis), and from parallel to spread apart in a pie
shape. In one embodiment, the SQUID, gradiometer, and driving transformer
(controller) have values of 1.8, 1.5 and 0.3 micro-Henrys, respectively.
The Helmholtz coil may have a sensitivity of 0.5 Gauss per amp at the
sweet spot.

[0157]Approximately 10 to 15 microvolts may be needed for a stochastic
response. By injecting Gaussian white noise stimulus, the system has
raised the sensitivity of the SQUID device. The SQUID device had a
sensitivity of about 5 femtotesla without the noise. This system has been
able to improve the sensitivity by 25 to 35 dB by injecting noise and
using this stochastic resonance response, which amounts to nearly a
1,500% increase.

[0158]After receiving and recording signals from the system, a computer,
such as a mainframe computer, supercomputer or high-performance computer
does both pre and post processing, such by employing the Autosignal
software product by Systat Software of Richmond Calif., for the
pre-processing, while Flexpro software product does the post-processing.
Flexpro is a data (statistical) analysis software supplied by Dewetron,
Inc. The following equations or options may be used in the Autosignal and
Flexpro products.

[0159]A flow diagram of the signal detection and processing performed by
the system 100 is shown in FIG. 8. When a sample is of interest, at least
four signal detections or data runs are performed: a first data run at a
time t1 without the sample, a second data run at a time t2 with
the sample, a third data run at a time t3 with the sample, and a
fourth data run at a time t4 without the sample. Performing and
collecting data sets from more than one data run increases accuracy of
the final (e.g., correlated) data set. In the four data runs, the
parameters and conditions of the system 100 are held constant (e.g.,
temperature, amount of amplification, position of the coils, the Gaussian
white noise stimulus signal, etc.).

[0160]At block 300, the appropriate sample (or if it's a first or fourth
data run, no sample), is placed in the system 100. A given sample,
without injected Gaussian white noise stimulus, emits electromagnetic
emissions in the DC-50 kHz range at an amplitude equal to or less than
approximately 0.001 microTesla. To capture such low emissions, Gaussian
white noise stimulus is injected at block 301.

[0161]At block 302, the coils 722, 724 detect the induced voltage
representative of the sample's emission and the injected Gaussian white
noise stimulus. The induced voltage comprises a continuous stream of
voltage values (amplitude and phase) as a function of time for the
duration of a data run. A data run can be 2-20 minutes in length and
hence, the data set corresponding to the data run comprises 2-20 minutes
of voltage values as a function of time.

[0162]At block 304, the injected Gaussian white noise stimulus is
cancelled as the induced voltage is being detected. This block is omitted
when the noise cancellation feature of the SQUID 206 is turned off.

[0163]At block 306, the voltage values of the data set are amplified by
20-50 dB, depending on whether noise cancellation occurred at the block
304. And at- block 308, the amplified data set undergoes analog to
digital (A/D) conversion and is stored in the recorder 212. A digitized
data set can comprise millions of rows of data.

[0164]After the acquired data set is stored, at a block 310 a check is
performed to see whether at least four data runs for the sample have
occurred (e.g., have acquired at least four data sets). If four data sets
for a given sample have been obtained, then lowpass filtering occurs at
block 312. Otherwise, the next data run is initiated (return to the block
300).

[0166]Next, at block 318, like data sets are correlated with each other at
each data point. For example, the first data set corresponding to the
first data run (e.g., a baseline or ambient noise data run) and the
fourth data set corresponding to the fourth data run (e.g., another noise
data run) are correlated to each other. If the amplitude value of the
first data set at a given frequency is the same as the amplitude value of
the fourth data set at that given frequency, then the correlation value
or number for that given frequency would be 1.0. Alternatively, the range
of correlation values may be set at between 0-100. Such correlation or
comparison also occurs for the second and third data runs (e.g., the
sample data runs). Because the acquired data sets are stored, they can be
accessed at a later time as the remaining data runs are completed.

[0167]Predetermined threshold levels are applied to each correlated data
set to eliminate statistically irrelevant correlation values. A variety
of threshold values may be used, depending on the length of the data runs
(the longer the data runs, greater the accuracy of the acquired data) and
the likely similarity of the sample's actual emission spectrum to other
types of samples. In addition to the threshold levels, the correlations
are averaged. Use of thresholds and averaging correlation results in the
injected Gaussian white noise stimulus component becoming very small in
the resulting correlated data set.

[0168]Once the two sample data sets have been refined to a correlated
sample data set and the two noise data sets have been refined to a
correlated noise data set, the correlated noise data set is subtracted
from the correlated sample data set. The resulting data set is the final
data set (e.g., a data set representative of the emission spectrum of the
sample) (block 320).

[0169]Since there can be 8600 data points per Hz and the final data set
can have data points for a frequency range of DC-50 kHz, the final data
set can comprise several hundred million rows of data. Each row of data
can include the frequency, amplitude, phase, and a correlation value.

III. Method of Identifying Candidate Optimal Time-Domain Signals

[0170]The signals produced in accordance with the methods described above
may be further selected for optimal effector activity, when used to
transduce an in vitro or mammalian system. According to one aspect of the
invention, it has been discovered that sample-dependent signal features
in a low-frequency time-domain signal obtained for a given sample can be
optimized by recording time-domain signals for sample over a range of
magnetic-field stimulus conditions, e.g., different voltage levels for
Gaussian white noise stimulus amplitudes and DC offsets. The recorded
signals are then processed to reveal signal features, and one or more
time domain signals having an optimal signal-analysis score, as detailed
below, are selected. The selection of optimized or near-optimized
time-domain signals is useful because it has been found, also in
accordance with the invention, that transducing an in vitro or biological
system with an optimized time-domain signal gives a stronger and more
predictable response than with a non-optimized time-domain signal. Viewed
another way, selecting an optimized (or near-optimized) time-domain
signal is useful in achieving reliable, detectable sample effects when a
target system is transduced by the sample signal.

[0171]In general, the range of injected white noise, DC offset, and sweep
amplitude voltages applied to the sample are such as to produce a
calculated magnetic field at the sample container of between 0 to 1 G
(Gauss), or alternatively, the injected noise stimulus is preferably
between about 30 to 35 decibels above the molecular electromagnetic
emissions sought to be detected, e.g., in the range 70-80-dbm. The number
of samples that are recorded, that is, the number of noise-level
intervals over which time-domain signals are recorded may vary from
10-100 or more, typically, and in any case, at sufficiently small
intervals so that a good optimum signal can be identified. For example,
the power gain of the noise generator level can be varied over 50 20 mV
intervals. As will be seen below, when the signal-analysis scores for the
signals are plotted against level of injected noise stimulus, the plot
shows a peak extending over several different noise levels when the
noise-level increments are suitable small.

[0172]Alternatively, stimulus signals other than Gaussian white noise can
be used for optimization of the recorded time-domain signal. Examples of
such signals include scanning a range of sine wave frequencies, a square
wave, time-series data containing defined non-linear structure, or the
SQUID output itself. These signals may themselves be pulsed between off
and on states to further modify the stimulus signal. The white noise
naturally generated by the magnetic shields may also be used as the
source of the stimulus signal.

[0173]The present invention contemplates five different methods for
calculating signal-analysis scores for the recorded time-domain signals.
These are (A) a histogram bin method, (B) generating an FFT of
autocorrelated signals, (C) averaging of FFTs, (D) use of a
cross-correlation threshold, and (E) phase-space comparison. Each of
these is detailed below

[0174]Although not specifically described, it will be appreciated that
each method may be carried out in a manual mode, where the user evaluates
the spectra on which a signal-analysis score is based, makes the noise
stimulus level adjustment for the next recording, and determines when a
peak score is reached, or it may be carried out in an automated or
semi-automated mode, in which the continuous incrementing of noise
stimulus level and/or the evaluation of signal-analysis score, is
performed by a computer-driven program.

A. Histogram Method of Generating Spectral Information

[0175]FIG. 9 is a high level data flow diagram in the histogram method for
generating spectral information. Data acquired from the SQUID (box 2002)
or stored data (box 2004) is saved as 16 bit WAV data (box 2006), and
converted into double-precision floating point data (box 2008). The
converted data may be saved (box 2010) or displayed as a raw waveform
(box 2012). The converted data is then passed to the algorithm described
below with respect to FIG. 10, and indicated by the box 2014 labeled
Fourier Analysis. The histogram can be displayed at 2016.

[0176]With reference to FIG. 10, the general flow of the histogram
algorithm is to take a discrete sampled time-domain signal and use
Fourier analysis to convert it to a frequency domain spectrum for further
analysis. The time-domain signals are acquired from an ADC
(analog/digital converter) and stored in the buffer indicated at 2102.
This sample is SampleDuration seconds long, and is sampled at SampleRate
samples per second, thus providing SampleCount
(SampleDuration*SampleRate) samples. The FrequencyRange that can be
recovered from the signal is defined as half the SampleRate, as defined
by Nyquist. Thus, if a time-series signal is sampled at 10,000 samples
per second, the FrequencyRange will be 0 Hz to 5 kHz. One Fourier
algorithm that may be used is a Radix 2 Real Fast Fourier Transform
(RFFT), which has a selectable frequency domain resolution (FFTSize) of
powers of two up to 216. An FFTSize of 8192 is selected, to provide
provides enough resolution to have at least one spectrum bin per Hertz as
long as the FrequencyRange stays at or below 8 kHz. The SampleDuration
should be long enough such that SampleCount>(2*) FFTSize*10 to ensure
reliable results.

[0177]Since this FFT can only act on FFTSize samples at a time, the
program must perform the FFT on the samples sequentially and average the
results together to get the final spectrum. If one chooses to skip
FFTSize samples for each FFT, a statistical error of 1/FFTSize 0.5 is
introduced. If, however, one chooses to overlap the FFT input by half the
FFTSize, this error is reduced to 1/(0.81*2*FFTSize) 0.5. This reduces
the error from 0.0110485435 to 0.0086805556. Additional information about
errors and correlation analyses in general, consult Bendat & Piersol,
"Engineering Applications of Correlation and Spectral Analysis", 1993.

[0178]Prior to performing the FFT on a given window, a data tapering
filter may be applied to avoid spectral leakage due to sampling aliasing.
This filter can be chosen from among Rectangular (no filter), Hamming,
Hanning, Bartlett, Blackman and Blackman/Harris, as examples.

[0179]In an exemplary method, and as shown in box 2104, we have chosen
8192 for the variable FFTSize, which will be the number of time-domain
samples we operate on at a time, as well as the number of discrete
frequencies output by the FFT. Note that FFTSize=8192 is the resolution,
or number of bins in the range which is dictated by the sampling rate.
The variable n, which dictates how many discrete RFFT's (Real FFT's)
performed, is set by dividing the SampleCount by FFTSize*2, the number of
FFT bins. In order for the algorithm to generate sensible results, this
number n should be at least 10 to 20 (although other valves are
possible), where more may be preferred to pick up weaker signals. This
implies that for a given SampleRate and FFTSize, the SampleDuration must
be long enough. A counter m, which counts from 0 to n, is initialized to
zero, also as shown in box 2104.

[0180]The program first establishes three buffers: buffer 2108 for FFTSize
histogram bins, that will accumulate counts at each bin frequency; buffer
2110 for average power at each bin frequency, and a buffer 2112
containing the FFTSize copied samples for each m.

[0181]The program initializes the histograms and arrays (box 2113) and
copies FFTSize samples of the wave data into buffer 2112, at 2114, and
performs an RFFT on the wave data (box 2115). The FFT is normalized so
that the highest amplitude is 1 (box 2116) and the average power for all
FFTSize bins is determined from the normalized signal (box 2117). For
each bin frequency, the normalized value from the FFT at that frequency
is added to each bin in buffer 2108 (box 2118).

[0182]In box 2119 the program then looks at the power at each bin
frequency, relative to the average power calculated from above. If the
power is within a certain factor epsilon (between 0 and 1) of the average
power, then it is counted and the corresponding bin is incremented in the
histogram buffer at 16. Otherwise it is discarded.

[0183]Note that the average power it is comparing to is for this FFT
instance only. An enhanced, albeit slower algorithm might take two passes
through the data and compute the average over all time before setting
histogram levels. The comparison to epsilon helps to represent a power
value that is significant enough for a frequency bin. Or in broader
terms, the equation employing epsilon helps answer the question, "is
there a signal at this frequency at this time?" If the answer is yes, it
could due be one of two things: (1) stationary noise which is landing in
this bin just this one time, or (2) a real low level periodic signal
which will occur nearly every time. Thus, the histogram counts will weed
out the noise hits, and enhance the low level signal hits. So, the
averaging and epsilon factor allow one to select the smallest power level
considered significant.

[0184]Counter m is incremented at box 2120, and the above process is
repeated for each n set of WAV data until m is equal to n (box 2121). At
each cycle, the average power for each bin is added to the associated bin
at 2118, and each histogram bin is incremented by one when the power
amplitude condition at 2114 is met.

[0185]When all n cycles of data have been considered, the average power in
each bin is determined by dividing the total accumulated average power in
each bin by n, the total number of cycles (box 2122) and the results
displayed (box 2123). Except where structured noise exists, e.g., DC=0 or
at multiples of 60 Hz, the average power in each bin will be some
relatively low number.

[0186]The relevant settings in this method are noise stimulus gain and the
value of epsilon. This value determines a power value that will be used
to distinguish an event over average value. At a value of 1, no events
will be detected, since power will never be greater than average power.
As epsilon approaches zero, virtually every value will be placed in a
bin. Between 0 and 1, and typically at a value that gives a number of bin
counts between about 20-50% of total bin counts for structured noise,
epsilon will have a maximum "spectral character," meaning the stochastic
resonance events will be most highly favored over pure noise.

[0187]Therefore, one can systematically increase the power gain on the
magnetic-field stimulus input, e.g., in 50 mV increments between 0 and 1
V, and at each power setting, adjust epsilon until a histogram having
well defined peaks is observed. Where, for example, the sample being
processed represents a 20 second time interval, total processing time for
each different power and epsilon will be about 25 seconds. When a
well-defined signal is observed, either the power setting or epsilon or
both can be refined until an optimal histogram, meaning one with the
largest number of identifiable peaks, is produced.

[0188]Under this algorithm, numerous bins may be filled and associated
histogram rendered for low frequencies due to the general occurrence of
noise (such as environmental noise) at the low frequencies. Thus, the
system may simply ignore bins below a given frequency (e.g., below 1
kHz), but still render sufficient bin values at higher frequencies to
determine unique signal signatures between samples.

[0189]Alternatively, since a purpose of the epsilon variable is to
accommodate different average power levels determined in each cycle, the
program could itself automatically adjust epsilon using a predefined
function relating average power level to an optimal value of epsilon.

[0190]Similarly, the program could compare peak heights at each power
setting, and automatically adjust the noise stimulus power setting until
optimal peak heights or character is observed in the histograms.

[0191]Although the value of epsilon may be a fixed value for all
frequencies, it is also contemplated to employ a frequency-dependent
value for epsilon, to adjust for the higher value average energies that
may be observed at low frequencies, e.g., DC to 1,000. A
frequency-dependent epsilon factor could be determined, for example, by
averaging a large number of low-frequency FFT regions, and determining a
value of epsilon that "adjusts" average values to values comparable to
those observed at higher frequencies.

B. FFT of Autocorrelated Signals

[0192]In a second general method for determining signal-analysis scores,
time-domain signals recorded at a selected noise stimulus are
autocorrelated, and a fast Fourier transform (FFT) of the autocorrelated
signal is used to generate a signal-analysis plot, that is, a plot of the
signal in the frequency domain. The FFTs are then used to score the
number of spectral signals above an average noise level over a selected
frequency range, e.g., DC to 1 kHz or DC to 8 kHz.

[0193]FIG. 11 is a flow diagram of steps carried out in scoring recorded
time-domain signals according to this second embodiment. Time-domain
signals are sampled, digitized, and filtered as above (box 402), with the
gain on the magnetic-field stimulus level set to an initial level, as at
404. A typical time domain signal for a sample compound 402 is
autocorrelated, at 408, using a standard autocorrelation algorithm, and
the FFT of the autocorrelated function is generated, at 410, using a
standard FFT algorithm.

[0194]An FFT plot is scored, at 412, by counting the number of spectral
peaks that are statistically greater than the average noise observed in
the autocorrelated FFT and the score is calculated at 414. This process
is repeated, through steps 416 and 406, until a peak score is recorded,
that is, until the score for a given signal begins to decline with
increasing noise stimulus gain. The peak score is recorded, at 418, and
the program or user selects, from the file of time-domain signals at 422,
the signal corresponding to the peak score (box 420).

[0195]As above, this embodiment may be carried out in a manual mode, where
the user manually adjusts the noise stimulus setting in increments,
analyzes (counts peaks) from the FFT spectral plots by hand, and uses the
peak score to identify one or more optimal time-domain signals.
Alternatively, one or more aspects of the steps can be automated.

C. Averaged FFTs

[0196]In another embodiment for determining signal-analysis scores, an FFT
of many, e.g., 10-20 time domain signals at each noise stimulus gain are
averaged to produce a spectral-peaks plot, and scores are calculated as
above.

[0197]FIG. 12 is a flow diagram of steps carried out in scoring recorded
time-domain signals according to this third embodiment. Time-domain
signals are sampled, digitized, and filtered as above (box 424), with the
gain on the magnetic-field stimulus level set to an initial level, as at
426. The program then generates a series of FFTs for the time domain
signal(s) at each noise stimulus gain, at 428, and these plots are
averaged at 430. Using the averaged FFT plot, scoring is done by counting
the number of spectral peaks that are statistically greater than the
average noise observed in the averaged FFT, as at 432, 434. This process
is repeated, through the logic of 436 and 437, until a peak score is
recorded, that is, until the score for a given signal begins to decline
with increasing magnetic-field stimulus gain. The peak score is recorded,
at 438, and the program or user selects, from the file of time-domain
signals at 442, the signal corresponding to the peak score (box 440).

[0198]As above, this method may be carried out in a manual,
semi-automated, or fully automated mode.

D. Cross-Correlation Threshold

[0199]In another embodiment for determining signal-analysis scores, a
cross-correlation algorithm is used in conjunction with a threshold.
First, the response time-series data is offset such that its mean is
zero, by calculating its mean value and subtracting that value from the
whole of the data. Then, a block of data of duration Tau is extracted
from near the beginning of this time-series data, and a cross-correlation
performed with the remainder of the dataset. The algorithm for the
cross-correlation is well-known. The cross-correlation output is used to
calculate a standard deviation value. The algorithm for calculating the
standard deviation is well-known. This standard deviation is then
multiplied by a factor called Alpha, which is typically 2.0, to generate
a threshold value. The cross-correlation output is then compared against
this threshold value, and the number of times the cross-correlation
output exceeds the threshold value is counted. The count value is the
score for that response time-series data.

[0200]This method of calculating the score for response times-series data
provides a measure of how often a data pattern contained within the Tau
data block is repeated in the remainder of the data, and thus constitutes
a measure of how much data pattern is being produced by the sample.

[0201]The score can be calculated for response time-series by data for a
range of Tau durations, to ensure appropriate capture of data patterns
produced by the sample.

[0202]Score values can be calculated for a sample under varying
conditions, such as varying stimulus Gaussian white noise amplitude or
offset. Comparison of the resulting set of score values enables
identification of the sample conditions that produce the strongest data
patterns from the sample. Those conditions can then be used for acquiring
data for use in effecting chemical or biological systems.

[0203]In one embodiment, the system extracts time series data from a
WAV-format file, representing the SQUID data recorded (for typically 60
s) from a MIDS unit. A block of data of duration Tau (typically 5 to 20
ms) is taken from near the beginning of the time series, and a
cross-correlation is performed with the remainder of the data, yielding a
cross-correlation dataset.

CrossCorrelation Details

[0204]The cross correlation Rxy(t) of the signals x(t) and y(t) is defined
as

[0205]The discrete implementation of the CrossCorrelation VI is as
follows. Let h represent a sequence whose indexing can be negative, let n
be the number of elements in the input sequence X, let m be the number of
elements in the sequence Y, and assume that the indexed elements of X and
Y that lie outside their range are equal to zero,

for i=0, 1, 2, . . . , size-1, size=n+m-1,where size is the number of
elements in the output sequence Rxy.

[0206]Then, the mean of this cross-correlation dataset is calculated, and
multiplied by a factor Alpha (typically 1.1), to create a threshold
value. The total number of times that the cross-correlation dataset
crosses the threshold value is counted, and this count is output as the
Score value.

[0207]The Score value is essentially a measure of how spiky the
cross-correlation dataset is, and thus is a measure of how often a
pattern (of duration Tau) in the initial data block is repeated in the
subsequent data.

[0208]Since such a repetitive pattern may or may not exist in the initial
data block, the position and size of the initial data block are varied to
determine the statistical significance of resultant Score values.

[0209]An example Score result is shown in FIG. 13. The upper graph shows
File # on the X-axis, Tau on the Y-axis, and Score on the Z-axis. The
File # corresponds to a sequence of files accumulated with varying
acquisition parameters; in this example, the MIDS stimulus offset is
repeatedly incremented from +100 mV to +250 mV nine times. The Tau refers
to the duration of the initial data block, which is incremented to ensure
capture of any data patterns. The Score at each X,Y coordinate in
indicated by a color map; in this example, a score of 0 is black, 5000 is
blue, and 10000 is white, with intermediate values indicated by
intermediate colors.

[0210]The user can manually move the red cursor around to slice through
the intensity graph either horizontally or vertically; in this example,
it is sliced horizontally, and the data across the slice is presented in
the lower linear graph.

[0211]The lower linear graph indicates how the Score value changes. In
this example, it shows how the Score typically is higher for files
acquired with MIDS offsets in the range of +105 mV to +130 mV, a motif
that repeats itself nine times in synchronization with the repetition of
the offset incrementation. This indicates a data pattern (of unknown
structure) present for the +105 mV to +130 mV offsets that is not present
for the remaining offsets.

E. Phase-Space Comparison

[0212]In another embodiment for determining signal-analysis scores, a
phase-space is computed for the response time-series data, and this
phase-space correlated with the phase-space from another time-series
data. First, the response time-series data is used to compute Average
Mutual Information. The algorithm for Average Mutual Information is
well-known. The first minimum corresponds to an optimal Tau value. This
Tau value is then used to compute an N-dimensional phase space using
Takens' Theorem. The algorithm for Takens' Theorem is well-known.

[0213]The resulting phase-space structure is then compared with the
phase-space structure from another time-series. The comparison would
typically be between data acquired with sample present and sample absent,
or between sample present and solvent-only present.

[0214]The comparison is performed by comparing the phase-space densities
throughout the phase-space region. This is computed by calculating the
weighted average of the absolute value of a quotient formed by dividing
the natural logarithm of the probability array S by the probability array
R. The probability arrays S and R are formed by binning the Sample phase
space and the Reference phase space into a finite number of bins, then
normalizing to 1. The output of the comparison is the score value.

[0215]Score values can be calculated for a sample under varying
conditions, such as varying Gaussian white noise stimulus amplitude or
offset. Comparison of the resulting set of score values enables
identification of the sample conditions that produce the strongest data
patterns from the sample. Those conditions can then be used for acquiring
data for use in effecting chemical or biological systems. First, the
incoming time series data ("Voltage Array in") is scaled so that its
values are in the range of zero up to "Phase Space Size", which is
typically 1000. Then, these values are discretized to integers. These
integers are then used as indices of a two-dimensional array, the Phase
Space, which is typically 1000×1000. Pairs of integers that are
separated by a duration "Tau" are used to specify an X,Y location in the
Phase Space, and the value at that location is incremented by a value of
1. All possible such pairs of integers are used by sliding along the time
series data, which generates a net pattern in the Phase Space.

[0216]To compare two different Phase Spaces, such as from a sample and a
reference, the two Phase Spaces (Sample Array and Reference Array) are
normalized by dividing by their sums, to yield Ps(xyz) and Pr(xyz),
respectively. Each element within the arrays is then used to compute a
net difference:

[0217]The difference represents a Score value for the specific data
acquisition conditions, such as a given stimulus noise amplitude and
offset. Applying this Difference calculation to a set of data spanning a
range of amplitudes and offsets thus provides a set of Score values. The
highest Score value indicates where the sample has had the greatest
non-linear influence on the data, and thus suggests it's effectiveness in
biological transduction.

[0218]Of the five scoring algorithms, the preference is for (i) the FFT
autocorrelation method (Algorithm B), (ii) the phase-space comparison
(Algorithm E), or (iii) the histogram method (Algorithm A).

IV. Transduction Apparatus and Protocols

[0219]This section describes equipment and methodology for transducing a
sample with signals generated and selected according to the methods
described in Sections I and II above. The signals employed in these
experiments, which are optimized time-domain signals formed in accordance
with the method described above demonstrate the ability of signals in
accordance with the invention to produce a compound-specific response in
various in vitro or mammalian systems.

[0220]FIG. 14 shows the layout of equipment for transducing a sample with
an agent-specific signal, in accordance with the invention. The
particular layout accommodates five different samples, including three
samples 444, 446, and 448 which are held within transduction coils, and
exposed to electromagnetic signals, a sample 450 that serves as a
control, and a sample 452 that serves as a chemical-induction control.
The system of FIG. 15 may be used for experimentation; if used for
treating a patient, then some elements may be omitted, such as 448, 450,
452, etc.

[0221]Transduction by an agent-specific signal is carried out by "playing"
the optimized agent-specific signal to the sample, using, where the
signal is recorded on a CD, and is played on a CD recorded 454 through a
preamplifier 456 and an audio amplifier 458. This signal is supplied to
the electromagnetic coils 444 and 446 through separate channels, as
shown. In one embodiment, a Sony Model CDP CE375 CD Player is used.
Channel 1 of the Player is connected to CD input 1 of Adcom Pre Amplifier
Model GFP 750. Channel 2 is connected to CD input 2 of Adcom Pre
Amplifier Model GFP 750. CD's are recorded to play identical signals from
each channel. Alternatively, CD's may be recorded to play different
signals from each channel. The coil in sample 448 is used primarily to
produce a Gaussian white noise field as a control for experiments. For
example, a GR analog noise generator provides a Gaussian white noise
source for this coil. Alternatively, this coil can be used to play any
pre recorded transduction signal via a second Crown amplifier.

[0222]FIG. 15 shows sample transduction equipment 466 such as represented
by any of samples 444, 446, and 448 in FIG. 14. The equipment includes a
chamber 468 housing an electromagnet 470, and various probes for
monitoring conditions within the chamber, e.g., temperature. The
electromagnet sits on a base 474, and includes, conventionally a toroidal
ferromagnetic core and wire windings.

[0223]The electromagnet may have one or more windings for the purpose of
controlling its magnetic field magnitude, gradient, and orientation in
the region where the sample is placed.

[0224]In one embodiment of the transduction equipment, the coils are
engineered and manufactured by American Magnetics to provide uniform
performance between coils. Each coil consists of 416 turns of #8 gauge
(awg) square copper magnet wire, enamel coated, with about a diameter 2''
air core. Each coil can produce approximately 1500 Gauss in the center at
10 Volts RMS at 10 Amps RMS at 11 Hertz without exceeding a 15 degree
Celsius rise in temperature.

[0225]In a second embodiment of the transduction equipment, suitable for
use where the transducing component is a low-field NMR signal, or
contains NMR components, a pair of coils may be axially separated by
approximately the same distance as the diameter, forming a Helmholtz
configuration. Electric current circulates in the same direction in both
coils. This configuration optimizes the magnetic field uniformity in the
vicinity of the center of the pair.

[0226]In a third embodiment of the transduction equipment, also suitable
for use where the transducing component is a low-field NMR signal, or
contains NMR components, two pairs of Helmholtz coils are wound on top of
each other, where one pair has electric current circulating in the same
direction in both coils, and the other pair has electric current
circulating in opposite directions. This configuration produces a
controlled magnetic field gradient, as well as a controlled magnetic
field magnitude.

[0227]In another general embodiment of the transduction equipment, several
Helmholtz coil pairs may be constructed to be orthogonal to one another.
This configuration would allow considerable flexibility in controlling
the structure of the magnetic field applied to a sample. For example, a
static magnetic field could be applied along one axis, and a varying
magnetic field applied along another axis. Such a configuration would be
useful for applying NMR-type signals to biological systems. A static
field of 7 microTesla would be generated by a constant current through
the first coil, and a varying magnetic field of lesser amplitude would be
generated by a varying current through the second coil. The varying
current would be generated by a set of sine waves added together, where
the sine wave have frequencies corresponding to the calculated NMR
spectrum at 7 microTesla.

[0228]The transduction equipment may be placed in a shielded enclosure for
the purpose of minimizing uncontrolled extraneous fields from the
environment in the region where the sample is placed.

[0229]In one embodiment of the shielding, the transduction equipment is
located within a much larger enclosure, a least 3 times larger than the
transduction equipment. This large container is lined with copper mesh
attached to Earth ground. Such a container is commonly called a "Faraday
cage". The copper mesh attenuates external environmental electromagnetic
signals that are greater than approximately 10 kHz.

[0230]In a second embodiment of the shielding, the transduction equipment
is located within a large enclosure constructed of sheet aluminum or
other solid conductor with minimal structural discontinuities. Such a
container attenuates external environmental electromagnetic signals that
are greater than approximately 1 kHz.

[0231]In a third embodiment of the shielding, the transduction equipment
is located within a very large set of three orthogonal Helmholtz coil
pairs, at least 5 times larger than the transduction equipment. A
fluxgate magnetic sensor container is located near the geometric center
of the Helmholtz coil pairs, and somewhat distant from the transduction
equipment. Signal from the fluxgate sensor is input to a feedback device,
such as a Lindgren, Inc. Magnetic Compensation System, and a feedback
current used to drive the Helmholtz coils, forcing a region within the
Helmholtz coils to be driven to zero field. Since the Helmholtz coil
pairs are very large, this region is also correspondingly large.
Furthermore, since the transduction equipment uses relatively small
coils, their field does not extend outward sufficiently to interfere with
the fluxgate sensor. Such a set of Helmholtz coil pairs attenuates
external environmental electromagnetic signals between 0.001 Hz and 1
kHz.

[0232]In a fourth embodiment of the shielding, the transduction equipment
may be located in either a copper mesh or aluminum enclosure as mentioned
above, and that enclosure itself located within the set of Helmholtz coil
pairs mentioned above. Such a configuration can attenuate external
environmental electromagnetic signals over their combined ranges.

[0233]In operation, the sample, e.g., an in vitro system or a mammalian
subject or a selected target area of a mammalian subject, is placed
centrally within the coils of the transduction equipment. Thus, for
example, the coils may be at opposite ends of a support bed, or on
opposite sides of the bed, and on opposite sides of the patient's head.
The coil is then activated, using signal generation equipment like that
shown in FIG. 15, for transducing the system with agent-specific
time-domain signals, preferably selected by one of the scoring algorithms
described in Section III.

[0234]The transduction parameters, i.e., the selected transduction
conditions to which the system is exposed are (i) the voltage of the
applied time-domain signal, (ii) the duration of applied signal, and
(iii) the scheduling of the applied signal. The applied voltage may be
over a range from slightly greater than zero to up to about 100 Volts.
The time of application may be from a few minutes to up to several days.
The scheduling refers to the alternating periods of signal off and signal
on, where these alternating periods can be quite brief, e.g., only a few
second, where the signal is rapidly alternating between on and off
conditions, to expended periods, for example, several hours on and
several hours off.

[0235]As will be seen below, and in accordance with one aspect of the
invention, optimal effector time-domain signals, and optimized
transduction conditions for transducing a mammalian system can be
identified by transduction studies with a simplified in vitro analog of
the mammalian system.

V. Method for Generating a Time-Domain Signal Capable of Producing an
Agent-Specific Effect on a Mammalian System

[0236]Sections II and III above describe methods for generating
low-frequency, time-domain signals for an agent, e.g., compound known to
act as an effector in an in vitro or mammalian system, and for selecting
optimal time-domain signals from among those recorded. Briefly, as
detailed in Section II, an agent capable of effecting a mammalian system
is placed in a magnetically and electromagnetically shielded sample
container, a selected magnetic-field stimulus is applied to the sample,
e.g., by a Helmholtz coil surrounding the sample container, and a
low-frequency, time-domain signal composed of sample source radiation
superimposed on the injected stimulus magnetic field is recorded, e.g.,
by a SQUID in a cryogenic container, and signal recordings are made at
each of a plurality of different stimulus magnetic field conditions,
e.g., different noise or offset voltages. Typically between about 50 and
1,000 time-domain signals will provide an adequate set of signals from
which optimized signals for transducing a mammalian system can be found.
For example, the signal might be recorded at each of 50 different
magnetic-field stimulus conditions, at each of ten different sample
concentrations to produce 500 time-domain signals.

[0237]The plurality of low-frequency time-domain signals recorded for the
agent at different magnetic-stimulus condition, and optionally, at
different sample concentrations, are then analyzed by a scoring algorithm
that measures the number of low-frequency components above a given
threshold in a recorded signal, employing one of the scoring algorithms
described in Section III above. In this step, each time-domain signal,
representing a recording at a different selected magnetic-field stimulus
is scored, and those signals having the highest score--meaning the
highest number of low-frequency components above a given threshold in a
recorded signal--are identified as candidates from which optimal signals
capable of transducing an in vitro system can be identified. Typically,
between 3-10 signals having the highest scores are identified by this
scoring method.

[0238]In accordance with one aspect of the invention, the time-domain
signals identified by the scoring algorithm above may be further selected
for effectiveness in a mammalian system by testing each of the
high-scoring signals in an in vitro system designed to serve as a
simplified model that mirrors the interaction of the agent with a
biochemical target in a more complex mammalian system. As noted above,
the in vitro system may also be useful for identifying optimal
transduction parameters, including the signal voltage applied to the
transduction coils, the transduction time, and scheduling of system
exposure to the transduction signal.

[0239]In one example that has been the focus of a number of studies, the
effector agent is taxol (also known as paclitaxel), an anti-tumor agent
that is known is act by stimulating and stabilizing tubulin assembly into
microtubules. In vivo, taxol interferes with cellular microtubule
dynamics, causing cells to arrest in mitosis, interrupts intracellular
transport of cargo, disrupts cell shape, cell motility and distribution
of molecules on cell membranes. Thus, the ability of taxol to promote
assembly of tubulin in vitro is directly related to its mechanism of
action in vivo.

[0240]The in vitro test for selecting the most effective taxol-related
time-domain signal that was chosen was a standard tubulin aggregation
assay used for determining the tubulin assembly activity of an added
compound. This assay has been described, for example, in Shelanski, M.
L., Gaskin, F. and Cantor, C. R. (1973). Microtubule assembly in the
absence of added nucleotides. Proc. Natl. Acad. Sci. U.S.A. 70, 765-768;
and Lee, J. C. and Timasheff, S. N. (1977). In vitro reconstitution of
calf brain microtubules: effects of solution variable. Biochemistry, 16,
1754-1762.

[0241]The assay protocol was designed for performing a single assay in a
cuvette using a spectrophotometer set at 340 nm in a kinetic mode.
HTS-Tubulin was purchased from Cytoskeleton, Inc. and is supplied in
multiple vials as lyophilized protein. The lyophilized tubulin was
resuspended in tubulin polymerization buffer (GPEM) to a final
concentration of 1.5 mg/ml. Before starting the assay, the
spectrophotometer is set in a Kinetic Mode. Using a blank of tubulin
polymerization buffer, the spectrophotometer is zeroed at 340 nm. During
the assay the data is collected either every 10 secs, 30 secs or 60 secs
as needed. Averaging time was set to 1 sec. In the studies reported
below, the assay was carried out for 20 minutes.

[0242]In one group of in vitro tests, taxol-specific time-domain signals
were obtained by recording low-frequency signals from a sample of taxol
suspended in Cremophore® to a final concentration of 6 mg/ml. The
signals were recorded with injected DC offset, at noise level settings
between 10 and 241 mV and in increments of 1 mV. A total of 241
time-domain signals over this injected-noise level range were obtained,
and these were analyzed by the FFT autocorrelation algorithm detailed
above, yielding 8 time-domain taxol signals for further in vitro testing.
One of these, designated signal M2(3) was among the most effective of the
8 signals in the in vitro transduction studies described below.

[0243]The tubulin-assembly reaction was carried out by exposing the
tubulin in GPEM buffer, at a concentration of 1.5 mg/ml to the following
polymerization conditions: (i) a buffer (control), (ii) tubulin alone
(2nd control); (iii) taxol, added to a final concentration of 4 μM,
and (iv) the M2(3) taxol signal from above, transduced over a 20 minute
period at a transduction voltage calculated to produce an approximately
1.693294 mG magnetic field. Change in optical absorption at 340 nm was
measured continuously for each sample, and the OD340 data was used to
calculate a rate of tubulin polymerization (dA/minute at 340 nm) at each
one minute interval during the transduction study.

[0244]The results of the study, expressed as rate or tubulin
polymerization at time points 1, 2, 3, 4 and 5, minutes, are shown in the
bar graphs in FIGS. 16A-16F, respectively. In each figures M2(3)1,
M2(3)2, and M2(3)3 represent the same signal, but transduced in separate
transduction chambers under slightly different magnetic-field levels. The
data show that, even after only one minute, the M2(3) transduction signal
is effective to produce a significant increase in tubulin polymerization
rate relative to the two control, and even with when compared with taxol
itself (FIG. 16A). At two minutes (FIG. 16B), the rates of polymerization
of two of the three M2(3) signals increased significantly, as was true
for the taxol-containing sample as well. These trends continued for time
periods 3, 4, and 5, minutes, with the rate of polymerization due to
taxol itself overtaking the rate of tubulin polymerization by signal
transduction at 5 minutes.

[0245]The Vmax of the reaction was also calculated for each sample at the
end of the 20 minute assay period. Although the tubulin polymerization
assay is known to involve three separate events, each with different Vmax
values, a single composite Vmax value, representing the maximum rate of
reaction over the entire assay is determined, and these values are
plotted in FIG. 17. As seen, the control Vmax values were both between
about 0.2 and 0.3. Taxol, at a concentration of 4 μM, showed the
highest Vmax value, nearly 1.8, but two of the taxol-signal samples
were also high, slightly above 1.4. The third taxol-signal sample was
significantly lower, but still substantially above the control values.

[0246]A number of similar studies were carried out with transduction by
other taxol time-domain signals generated and identified according to the
methods detailed above. The results obtained were similar to those
described above, and although variations in the extent of tubulin
polymerization have been observed from signal to signal, and for the same
signal at different times, the same degree of variation was also observed
for taxol itself as the polymerizing agent. In addition, exposing the
tubulin sample to white noise did not produce tubulin assembly activity
statistically above control levels.

[0247]Based on the results from above, time-domain signal M2(3), and three
additional taxol-specific low-frequency time-domain signals that also
showed good activity in the tubulin in vitro assay were selected for
transduction studies in a mammalian system. The signals are identified in
FIG. 18 as signals A, B, C, and D (the M2(3) signal). In this study, five
groups of 10 mice each were each injected in the right frontal lobe with
5×105 U87 glioblastoma cells, and treatment with taxol signals
was begun one day later. The transduction device used in this study was a
2-ft diameter right-angle cylinder with coil windings. These cylinders
accommodate a standard mouse or rat cage so that mice are constantly
exposed to the MIDS playback of signals. During the treatment, all ten
mice in each group are housed in one cage and kept within the area of the
central cylindrical cavity of the large transduction coil under
continuous playback, while they are fed and watered. This results in a
continuous exposure duty time of about 90-95% of the study duration of 60
days. The treatment involved either no signal or one or the four
taxol-specific signals, applied to the coil by continuously sweeping the
signal over a magnetic-field of between 80-110 G, and sweep frequency of
1 sweep/sec, over the entire course of the study. That is, each signal is
played continuously to each of ten animals in a group, by sweeping the
signal over a selected magnetic-field range, with only occasional
interruption for cleaning and feeding.

[0248]The results of the study, plotted as number of animals surviving in
each group over the 60 day period, are plotted in FIG. 18. The effect of
taxol alone (the compound) was not examined in the study since it is
known to be poorly deliver to the brain, presumably because of inability
to pass the blood brain barrier effectively. As seen, all ten of the
animals in the control group died by day 34, and the same survival rate
was obtained for treatment by taxol signal A. However, both taxol signal
D, the time-domain signal shown above to promote tubulin assembly in the
tubulin polymerization assay, and taxol signal B gave significantly
improved survival times: mice in the signal-D group showed a 20% survival
rate out to day 46, and mice in the signal-B group gave showed a final
20% survival rate.

[0249]The results demonstrate that low-frequency time-domain signals, when
generated under a variety of selected magnetic-field injection
conditions, and selected by a scoring algorithm, then further selected in
an in vitro system that mimics the mechanism of action of the agent in a
mammalian system, can be used to mimic the effect of the agent itself on
the mammalian system.

[0250]The system for generating and selecting effective time-domain
signals has been illustrated above with respect to taxol and an in vitro
tubulin assembly assay, for selecting signals for producing a
taxol-related anti-tumor effect by signal transduction. It will be
appreciated that a variety of drugs used in treating mammalian diseases
have identified drug targets that can be modeled in an in vitro system to
identify drug-generated low-frequency time-domain signals that will be
effective in producing a similar drug-target interaction in a mammalian
host.

[0251]For example, a number of drugs that act to bind tubulin can be
similar tested for optimized time-domain signals by a similar in vitro
tubulin assay. Such drugs include, in addition to taxol, Docetaxel
(Taxotere), Epothilones, Discodermolide, Colchicine, Combretastatins,
2-Methoxyestradiol, Methoxybenzene-sulphonamide Estramustine, and the
vinca alkaloids, including Vinblastine (Velban), Vincristine (Oncovin),
Vinorelbine (Navelbine), Vinflunine, Cryptophycin, Halichondrins,
Dolastatins, and Hemiasterlins,

[0252]As another example, a large number of drugs function through their
ability to bind to specific cell receptors, e.g., G protein receptors.
For purposes of in vitro testing, there are many different mammalian
cells, often with a genetically altered genome designed for allowing
detection of agent binding to the target receptor, e.g., through the
expression of a recombinant fluorescent protein, that can be cultured
under conditions that would allow for the effects of signal transduction
of the cells to be observed. Thus, in this treatment model, the
transducing agent is the receptor-binding molecule, the in vitro system
is a cell-culture system that is responsive to agent binding to produce a
detectable cellular response, and the mammalian system is a mammalian
subject having a disease state that is amenable to treatment by the
binding agent.

[0253]Similarly, a number of drugs function through their ability to
inhibit the activity of a soluble or membrane-associated enzyme. For in
vitro testing, the target enzyme is likely to be adaptable to an in vitro
enzyme reaction assay in which a drug effect on the activity of the
enzyme can be detected, e.g., colorometrically, as an increase or
decrease in enzyme activity with respect to a detectable substrate. Thus,
in this treatment model, the transducing agent is the enzyme binding
agent, the in vitro system is an enzyme assay reaction which is
responsive to agent to produce a detectable change in enzyme kinetics,
and the mammalian system is a mammalian subject having a disease state
normally treated by the binding agent.

VI. Forming a Transduction NMR Signal

[0254]In one embodiment of the invention, the low-frequency signal that is
used to transduce a biological system (see below) is a low-frequency NMR
spectral signal of the transducing agent, e.g., therapeutic agent.

[0255]An NMR spectrum, e.g., conventional high-field NMR signal, consists
of a series of frequency bands that is characteristic of a sample
solution when placed in a static magnetic field of fixed magnitude. In
proton NMR, the Larmor frequency of hydrogen nuclei is split into the
frequency bands by spin coupling processes and local shielding effects
that occur within the sample molecule. For hydrogen nuclei, the
gyromagnetic ratio is 42.58 MHz/T, and thus in a typical NMR machine of 7
T, the Larmor frequency is (42.58 MHz/T)*(7 uT)=300 MHz, split into bands
that are several Hz apart. For hydrogen nuclei in a much weaker field of
7 uT, the Larmor frequency is (42.58 MHz/T)*(7 uT)=300 Hz, again split
into bands that are several Hz apart. Thus, if the field magnitude is
reduced, the frequency bands shift downwards by a corresponding amount,
but the splitting (from spin coupling processes) remains the same. Any
local shielding effects become negligible at lower field strengths.

[0256]To calculate the NMR spectrum at a low field strength using data
obtained in a high-field instrument, the following operations are carried
out. Assume, for example, that a high-field NMR instrument yields three
peaks at 1.03 ppm, 1.13 ppm, and 1.23 ppm in a 7 T magnetic field, due to
spin-coupling processes within a methyl group on a molecule, and that a
TMS standard yields a peak at 0.00 ppm. The frequencies of the methyl
bands relative to the TMS standard would be the ppm shift difference
multiplied by the Larmor frequency:

(1.03 ppm-0.00 ppm)*300000000 Hz=310 Hz

(1.13 ppm-0.00 ppm)*300000000 Hz=340 Hz

(1.23 ppm-0.00 ppm)*300000000 Hz=370 Hz

Since TMS theoretically has no significant chemical shift, the location of
its peak will be the simple Larmor frequency of 300000000 Hz. Thus, the
actual frequencies of the methyl group are:

300000000 Hz+310 Hz=300000310 Hz

300000000 Hz+340 Hz=300000340 Hz

300000000 Hz+370 Hz=300000370 Hz

If there were no chemical shift effect (such as in a low magnetic field),
then the frequencies of the methyl group would be centered on the Larmor
frequency, no longer shifted away from it. Thus, the methyl middle band
of would be centered on the Larmor frequency, and the two side bands
would be at +30 Hz and -30 Hz relative to the Larmor frequency:

370 Hz-340 Hz=+30 Hz

310 Hz-340 Hz=-30 Hz

The Larmor frequency in a 7 microTesla field is (42.58 MHz/T)*(7 uT)=300
Hz. Thus, the methyl group should exhibit a middle band at the Larmor
frequency, 300 Hz, and two side bands at 300 Hz+30 Hz=330 Hz and 300
Hz-30 Hz=270 Hz. The net spectrum of the methyl group would then be 330
Hz, 300 Hz, and 270 Hz.

[0257]This is the calculated NMR spectrum that should theoretically occur
in a 7 uT magnetic field. Note that this calculation is only valid for
low field strengths that are not so low that the final frequencies are
negative.

[0258]As an alternative approach, a low-frequency NMR signal of a given
agent may be generated directly by low-field NMR detection at millitesla
magnetic fields, and using an untuned superconducting quantum
interference device (SQUID) magnetometer (see above) to detect the
magnetic signals. That is, the signal-generating apparatus described
above, but operated in a low-field NMR mode, may be employed to directly
generate the low-field NMR signal.

[0259]Once the low-field NMR signal is calculated or generated, the
transduction signal may be constructed. This can be done by calculating
the inverse Fourier transform of the low-field NMR spectrum, to generate
time series data. This time series data can also be generated by adding
together a set of sine waves having the same frequencies and amplitudes
given in the low-field NMR spectrum. This time series data can then be
used to control the voltage of a suitable voltage generator. This
time-varying voltage can then be applied across a Helmholtz coil, whereby
electrical current flows through the conductor and generates a
time-varying magnetic field. This time-varying magnetic field is then
used for biological transduction.

[0260]In another embodiment of the invention, EPR (Electron Paramagnetic
Resonance) signals are used instead of NMR (Nuclear Magnetic Resonance)
signals. EPR involves electron spin--nuclear spin interactions, whereas
NMR involves nuclear spin--nuclear spin interactions. The procedures
outlined in this application for NMR data are functionally equivalent to
the procedures to be used for EPR data, except that EPR data is typically
at somewhat higher frequencies.

[0261]The above detailed description of embodiments of the invention is
not intended to be exhaustive or to limit the invention to the precise
form disclosed above. While specific embodiments of, and examples for,
the invention are described above for illustrative purposes, various
equivalent modifications are possible within the scope of the invention,
as those skilled in the relevant art will recognize. For example, while
processes or blocks are presented in a given order, alternative
embodiments may perform routines having steps, or employ systems having
blocks, in a different order, and some processes or blocks may be
deleted, moved, added, subdivided, combined, and/or modified. Each of
these processes or blocks may be implemented in a variety of different
ways. Also, while processes or blocks are at times shown as being
performed in series, these processes or blocks may instead be performed
in parallel, or may be performed at different times.

[0262]The teachings of the invention provided herein can be applied to
other systems, not necessarily the system described above. The elements
and acts of the various embodiments described above can be combined to
provide further embodiments.

[0263]All of the above patents and applications and other references,
including any that may be listed in accompanying filing papers, are
incorporated herein by reference. Aspects of the invention can be
modified, if necessary, to employ the systems, functions, and concepts of
the various references described above to provide yet further embodiments
of the invention.

[0264]These and other changes can be made to the invention in light of the
above Detailed Description. While the above description details certain
embodiments of the invention and describes the best mode contemplated, no
matter how detailed the above appears in text, the invention can be
practiced in many ways. Details of the signal processing system may vary
considerably in its implementation details, while still being encompassed
by the invention disclosed herein. As noted above, particular terminology
used when describing certain features or aspects of the invention should
not be taken to imply that the terminology is being redefined herein to
be restricted to any specific characteristics, features, or aspects of
the invention with which that terminology is associated. In general, the
terms used in the following claims should not be construed to limit the
invention to the specific embodiments disclosed in the specification,
unless the above Detailed Description section explicitly defines such
terms. Accordingly, the actual scope of the invention encompasses not
only the disclosed embodiments, but also all equivalent ways of
practicing or implementing the invention under the claims.